TY - JOUR A1 - Zhou, Lin A1 - Fischer, Eric A1 - Tunca, Can A1 - Brahms, Clemens Markus A1 - Ersoy, Cem A1 - Granacher, Urs A1 - Arnrich, Bert T1 - How We Found Our IMU BT - Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications JF - Sensors N2 - Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data. KW - inertial measurement unit KW - pervasive healthcare KW - gait analysis KW - comparison of devices Y1 - 2020 U6 - https://doi.org/10.3390/s20154090 SN - 1424-8220 VL - 20 IS - 15 PB - MDPI CY - Basel ER - TY - JOUR A1 - Trautmann, Justin A1 - Zhou, Lin A1 - Brahms, Clemens Markus A1 - Tunca, Can A1 - Ersoy, Cem A1 - Granacher, Urs A1 - Arnrich, Bert T1 - TRIPOD BT - A treadmill walking dataset with IMU, pressure-distribution and photoelectric data for gait analysis JF - Data : open access ʻData in scienceʼ journal N2 - Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data. KW - inertial measurement unit KW - gait analysis algorithm KW - OptoGait KW - Zebris KW - data pipeline KW - public dataset Y1 - 2021 U6 - https://doi.org/10.3390/data6090095 SN - 2306-5729 VL - 6 IS - 9 PB - MDPI CY - Basel ER - TY - GEN A1 - Trautmann, Justin A1 - Zhou, Lin A1 - Brahms, Clemens Markus A1 - Tunca, Can A1 - Ersoy, Cem A1 - Granacher, Urs A1 - Arnrich, Bert T1 - TRIPOD - A Treadmill Walking Dataset with IMU, Pressure-distribution and Photoelectric Data for Gait Analysis T2 - Postprints der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 6 KW - inertial measurement unit KW - gait analysis algorithm KW - OptoGait KW - Zebris KW - data pipeline KW - public dataset Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-522027 IS - 6 ER - TY - GEN A1 - Fehr, Jana A1 - Jaramillo-Gutierrez, Giovanna A1 - Oala, Luis A1 - Gröschel, Matthias I. A1 - Bierwirth, Manuel A1 - Balachandran, Pradeep A1 - Werneck-Leite, Alixandro A1 - Lippert, Christoph T1 - Piloting a Survey-Based Assessment of Transparency and Trustworthiness with Three Medical AI Tools T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Artificial intelligence (AI) offers the potential to support healthcare delivery, but poorly trained or validated algorithms bear risks of harm. Ethical guidelines stated transparency about model development and validation as a requirement for trustworthy AI. Abundant guidance exists to provide transparency through reporting, but poorly reported medical AI tools are common. To close this transparency gap, we developed and piloted a framework to quantify the transparency of medical AI tools with three use cases. Our framework comprises a survey to report on the intended use, training and validation data and processes, ethical considerations, and deployment recommendations. The transparency of each response was scored with either 0, 0.5, or 1 to reflect if the requested information was not, partially, or fully provided. Additionally, we assessed on an analogous three-point scale if the provided responses fulfilled the transparency requirement for a set of trustworthiness criteria from ethical guidelines. The degree of transparency and trustworthiness was calculated on a scale from 0% to 100%. Our assessment of three medical AI use cases pin-pointed reporting gaps and resulted in transparency scores of 67% for two use cases and one with 59%. We report anecdotal evidence that business constraints and limited information from external datasets were major obstacles to providing transparency for the three use cases. The observed transparency gaps also lowered the degree of trustworthiness, indicating compliance gaps with ethical guidelines. All three pilot use cases faced challenges to provide transparency about medical AI tools, but more studies are needed to investigate those in the wider medical AI sector. Applying this framework for an external assessment of transparency may be infeasible if business constraints prevent the disclosure of information. New strategies may be necessary to enable audits of medical AI tools while preserving business secrets. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 15 KW - artificial intelligence for health KW - quality assessment KW - transparency KW - trustworthiness Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-583281 IS - 15 ER - TY - JOUR A1 - Wiemker, Veronika A1 - Bunova, Anna A1 - Neufeld, Maria A1 - Gornyi, Boris A1 - Yurasova, Elena A1 - Konigorski, Stefan A1 - Kalinina, Anna A1 - Kontsevaya, Anna A1 - Ferreira-Borges, Carina A1 - Probst, Charlotte T1 - Pilot study to evaluate usability and acceptability of the 'Animated Alcohol Assessment Tool' in Russian primary healthcare JF - Digital health N2 - Background and aims: Accurate and user-friendly assessment tools quantifying alcohol consumption are a prerequisite to effective prevention and treatment programmes, including Screening and Brief Intervention. Digital tools offer new potential in this field. We developed the ‘Animated Alcohol Assessment Tool’ (AAA-Tool), a mobile app providing an interactive version of the World Health Organization's Alcohol Use Disorders Identification Test (AUDIT) that facilitates the description of individual alcohol consumption via culturally informed animation features. This pilot study evaluated the Russia-specific version of the Animated Alcohol Assessment Tool with regard to (1) its usability and acceptability in a primary healthcare setting, (2) the plausibility of its alcohol consumption assessment results and (3) the adequacy of its Russia-specific vessel and beverage selection. Methods: Convenience samples of 55 patients (47% female) and 15 healthcare practitioners (80% female) in 2 Russian primary healthcare facilities self-administered the Animated Alcohol Assessment Tool and rated their experience on the Mobile Application Rating Scale – User Version. Usage data was automatically collected during app usage, and additional feedback on regional content was elicited in semi-structured interviews. Results: On average, patients completed the Animated Alcohol Assessment Tool in 6:38 min (SD = 2.49, range = 3.00–17.16). User satisfaction was good, with all subscale Mobile Application Rating Scale – User Version scores averaging >3 out of 5 points. A majority of patients (53%) and practitioners (93%) would recommend the tool to ‘many people’ or ‘everyone’. Assessed alcohol consumption was plausible, with a low number (14%) of logically impossible entries. Most patients reported the Animated Alcohol Assessment Tool to reflect all vessels (78%) and all beverages (71%) they typically used. Conclusion: High acceptability ratings by patients and healthcare practitioners, acceptable completion time, plausible alcohol usage assessment results and perceived adequacy of region-specific content underline the Animated Alcohol Assessment Tool's potential to provide a novel approach to alcohol assessment in primary healthcare. After its validation, the Animated Alcohol Assessment Tool might contribute to reducing alcohol-related harm by facilitating Screening and Brief Intervention implementation in Russia and beyond. KW - Alcohol use assessment KW - Alcohol Use Disorders Identification Test KW - screening tools KW - digital health KW - mobile applications KW - Russia KW - primary healthcare KW - usability KW - acceptability Y1 - 2022 U6 - https://doi.org/10.1177/20552076211074491 SN - 2055-2076 VL - 8 PB - Sage Publications CY - London ER - TY - JOUR A1 - Fehr, Jana A1 - Piccininni, Marco A1 - Kurth, Tobias A1 - Konigorski, Stefan T1 - Assessing the transportability of clinical prediction models for cognitive impairment using causal models JF - BMC medical research methodology N2 - Background Machine learning models promise to support diagnostic predictions, but may not perform well in new settings. Selecting the best model for a new setting without available data is challenging. We aimed to investigate the transportability by calibration and discrimination of prediction models for cognitive impairment in simulated external settings with different distributions of demographic and clinical characteristics. Methods We mapped and quantified relationships between variables associated with cognitive impairment using causal graphs, structural equation models, and data from the ADNI study. These estimates were then used to generate datasets and evaluate prediction models with different sets of predictors. We measured transportability to external settings under guided interventions on age, APOE & epsilon;4, and tau-protein, using performance differences between internal and external settings measured by calibration metrics and area under the receiver operating curve (AUC). Results Calibration differences indicated that models predicting with causes of the outcome were more transportable than those predicting with consequences. AUC differences indicated inconsistent trends of transportability between the different external settings. Models predicting with consequences tended to show higher AUC in the external settings compared to internal settings, while models predicting with parents or all variables showed similar AUC. Conclusions We demonstrated with a practical prediction task example that predicting with causes of the outcome results in better transportability compared to anti-causal predictions when considering calibration differences. We conclude that calibration performance is crucial when assessing model transportability to external settings. KW - Alzheimer's Disease KW - Clinical risk prediction KW - DAG KW - Causality; KW - Transportability Y1 - 2023 U6 - https://doi.org/10.1186/s12874-023-02003-6 SN - 1471-2288 VL - 23 IS - 1 PB - BMC CY - London ER - TY - THES A1 - Jiang, Lan T1 - Discovering metadata in data files N2 - It is estimated that data scientists spend up to 80% of the time exploring, cleaning, and transforming their data. A major reason for that expenditure is the lack of knowledge about the used data, which are often from different sources and have heterogeneous structures. As a means to describe various properties of data, metadata can help data scientists understand and prepare their data, saving time for innovative and valuable data analytics. However, metadata do not always exist: some data file formats are not capable of storing them; metadata were deleted for privacy concerns; legacy data may have been produced by systems that were not designed to store and handle meta- data. As data are being produced at an unprecedentedly fast pace and stored in diverse formats, manually creating metadata is not only impractical but also error-prone, demanding automatic approaches for metadata detection. In this thesis, we are focused on detecting metadata in CSV files – a type of plain-text file that, similar to spreadsheets, may contain different types of content at arbitrary positions. We propose a taxonomy of metadata in CSV files and specifically address the discovery of three different metadata: line and cell type, aggregations, and primary keys and foreign keys. Data are organized in an ad-hoc manner in CSV files, and do not follow a fixed structure, which is assumed by common data processing tools. Detecting the structure of such files is a prerequisite of extracting information from them, which can be addressed by detecting the semantic type, such as header, data, derived, or footnote, of each line or each cell. We propose the supervised- learning approach Strudel to detect the type of lines and cells. CSV files may also include aggregations. An aggregation represents the arithmetic relationship between a numeric cell and a set of other numeric cells. Our proposed AggreCol algorithm is capable of detecting aggregations of five arithmetic functions in CSV files. Note that stylistic features, such as font style and cell background color, do not exist in CSV files. Our proposed algorithms address the respective problems by using only content, contextual, and computational features. Storing a relational table is also a common usage of CSV files. Primary keys and foreign keys are important metadata for relational databases, which are usually not present for database instances dumped as plain-text files. We propose the HoPF algorithm to holistically detect both constraints in relational databases. Our approach is capable of distinguishing true primary and foreign keys from a great amount of spurious unique column combinations and inclusion dependencies, which can be detected by state-of-the-art data profiling algorithms. N2 - Schätzungen zufolge verbringen Datenwissenschaftler bis zu 80% ihrer Zeit mit der Erkundung, Bereinigung und Umwandlung ihrer Daten. Ein Hauptgrund für diesen Aufwand ist das fehlende Wissen über die verwendeten Daten, die oft aus unterschiedlichen Quellen stammen und heterogene Strukturen aufweisen. Als Mittel zur Beschreibung verschiedener Dateneigenschaften können Metadaten Datenwissenschaftlern dabei helfen, ihre Daten zu verstehen und aufzubereiten, und so wertvolle Zeit die Datenanalysen selbst sparen. Metadaten sind jedoch nicht immer vorhanden: Zum Beispiel sind einige Dateiformate nicht in der Lage, sie zu speichern; Metadaten können aus Datenschutzgründen gelöscht worden sein; oder ältere Daten wurden möglicherweise von Systemen erzeugt, die nicht für die Speicherung und Verarbeitung von Metadaten konzipiert waren. Da Daten in einem noch nie dagewesenen Tempo produziert und in verschiedenen Formaten gespeichert werden, ist die manuelle Erstellung von Metadaten nicht nur unpraktisch, sondern auch fehleranfällig, so dass automatische Ansätze zur Metadatenerkennung erforderlich sind. In dieser Arbeit konzentrieren wir uns auf die Erkennung von Metadaten in CSV-Dateien - einer Art von Klartextdateien, die, ähnlich wie Tabellenkalkulationen, verschiedene Arten von Inhalten an beliebigen Positionen enthalten können. Wir schlagen eine Taxonomie der Metadaten in CSV-Dateien vor und befassen uns speziell mit der Erkennung von drei verschiedenen Metadaten: Zeile und Zellensemantischer Typ, Aggregationen sowie Primärschlüssel und Fremdschlüssel. Die Daten sind in CSV-Dateien ad-hoc organisiert und folgen keiner festen Struktur, wie sie von gängigen Datenverarbeitungsprogrammen angenommen wird. Die Erkennung der Struktur solcher Dateien ist eine Voraussetzung für die Extraktion von Informationen aus ihnen, die durch die Erkennung des semantischen Typs jeder Zeile oder jeder Zelle, wie z. B. Kopfzeile, Daten, abgeleitete Daten oder Fußnote, angegangen werden kann. Wir schlagen den Ansatz des überwachten Lernens, genannt „Strudel“ vor, um den strukturellen Typ von Zeilen und Zellen zu klassifizieren. CSV-Dateien können auch Aggregationen enthalten. Eine Aggregation stellt die arithmetische Beziehung zwischen einer numerischen Zelle und einer Reihe anderer numerischer Zellen dar. Der von uns vorgeschlagene „Aggrecol“-Algorithmus ist in der Lage, Aggregationen von fünf arithmetischen Funktionen in CSV-Dateien zu erkennen. Da stilistische Merkmale wie Schriftart und Zellhintergrundfarbe in CSV-Dateien nicht vorhanden sind, die von uns vorgeschlagenen Algorithmen die entsprechenden Probleme, indem sie nur die Merkmale Inhalt, Kontext und Berechnungen verwenden. Die Speicherung einer relationalen Tabelle ist ebenfalls eine häufige Verwendung von CSV-Dateien. Primär- und Fremdschlüssel sind wichtige Metadaten für relationale Datenbanken, die bei Datenbankinstanzen, die als reine Textdateien gespeichert werden, normalerweise nicht vorhanden sind. Wir schlagen den „HoPF“-Algorithmus vor, um beide Constraints in relationalen Datenbanken ganzheitlich zu erkennen. Unser Ansatz ist in der Lage, echte Primär- und Fremdschlüssel von einer großen Menge an falschen eindeutigen Spaltenkombinationen und Einschlussabhängigkeiten zu unterscheiden, die von modernen Data-Profiling-Algorithmen erkannt werden können. KW - data preparation KW - metadata detection KW - data wrangling KW - Datenaufbereitung KW - Datentransformation KW - Erkennung von Metadaten Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-566204 ER - TY - JOUR A1 - Rosin, Paul L. A1 - Lai, Yu-Kun A1 - Mould, David A1 - Yi, Ran A1 - Berger, Itamar A1 - Doyle, Lars A1 - Lee, Seungyong A1 - Li, Chuan A1 - Liu, Yong-Jin A1 - Semmo, Amir A1 - Shamir, Ariel A1 - Son, Minjung A1 - Winnemöller, Holger T1 - NPRportrait 1.0: A three-level benchmark for non-photorealistic rendering of portraits JF - Computational visual media N2 - Recently, there has been an upsurge of activity in image-based non-photorealistic rendering (NPR), and in particular portrait image stylisation, due to the advent of neural style transfer (NST). However, the state of performance evaluation in this field is poor, especially compared to the norms in the computer vision and machine learning communities. Unfortunately, the task of evaluating image stylisation is thus far not well defined, since it involves subjective, perceptual, and aesthetic aspects. To make progress towards a solution, this paper proposes a new structured, three-level, benchmark dataset for the evaluation of stylised portrait images. Rigorous criteria were used for its construction, and its consistency was validated by user studies. Moreover, a new methodology has been developed for evaluating portrait stylisation algorithms, which makes use of the different benchmark levels as well as annotations provided by user studies regarding the characteristics of the faces. We perform evaluation for a wide variety of image stylisation methods (both portrait-specific and general purpose, and also both traditional NPR approaches and NST) using the new benchmark dataset. KW - non-photorealistic rendering (NPR) KW - image stylization KW - style transfer KW - portrait KW - evaluation KW - benchmark Y1 - 2022 U6 - https://doi.org/10.1007/s41095-021-0255-3 SN - 2096-0433 SN - 2096-0662 VL - 8 IS - 3 SP - 445 EP - 465 PB - Springer Nature CY - London ER - TY - BOOK A1 - Kuban, Robert A1 - Rotta, Randolf A1 - Nolte, Jörg A1 - Chromik, Jonas A1 - Beilharz, Jossekin Jakob A1 - Pirl, Lukas A1 - Friedrich, Tobias A1 - Lenzner, Pascal A1 - Weyand, Christopher A1 - Juiz, Carlos A1 - Bermejo, Belen A1 - Sauer, Joao A1 - Coelh, Leandro dos Santos A1 - Najafi, Pejman A1 - Pünter, Wenzel A1 - Cheng, Feng A1 - Meinel, Christoph A1 - Sidorova, Julia A1 - Lundberg, Lars A1 - Vogel, Thomas A1 - Tran, Chinh A1 - Moser, Irene A1 - Grunske, Lars A1 - Elsaid, Mohamed Esameldin Mohamed A1 - Abbas, Hazem M. A1 - Rula, Anisa A1 - Sejdiu, Gezim A1 - Maurino, Andrea A1 - Schmidt, Christopher A1 - Hügle, Johannes A1 - Uflacker, Matthias A1 - Nozza, Debora A1 - Messina, Enza A1 - Hoorn, André van A1 - Frank, Markus A1 - Schulz, Henning A1 - Alhosseini Almodarresi Yasin, Seyed Ali A1 - Nowicki, Marek A1 - Muite, Benson K. A1 - Boysan, Mehmet Can A1 - Bianchi, Federico A1 - Cremaschi, Marco A1 - Moussa, Rim A1 - Abdel-Karim, Benjamin M. A1 - Pfeuffer, Nicolas A1 - Hinz, Oliver A1 - Plauth, Max A1 - Polze, Andreas A1 - Huo, Da A1 - Melo, Gerard de A1 - Mendes Soares, Fábio A1 - Oliveira, Roberto Célio Limão de A1 - Benson, Lawrence A1 - Paul, Fabian A1 - Werling, Christian A1 - Windheuser, Fabian A1 - Stojanovic, Dragan A1 - Djordjevic, Igor A1 - Stojanovic, Natalija A1 - Stojnev Ilic, Aleksandra A1 - Weidmann, Vera A1 - Lowitzki, Leon A1 - Wagner, Markus A1 - Ifa, Abdessatar Ben A1 - Arlos, Patrik A1 - Megia, Ana A1 - Vendrell, Joan A1 - Pfitzner, Bjarne A1 - Redondo, Alberto A1 - Ríos Insua, David A1 - Albert, Justin Amadeus A1 - Zhou, Lin A1 - Arnrich, Bert A1 - Szabó, Ildikó A1 - Fodor, Szabina A1 - Ternai, Katalin A1 - Bhowmik, Rajarshi A1 - Campero Durand, Gabriel A1 - Shevchenko, Pavlo A1 - Malysheva, Milena A1 - Prymak, Ivan A1 - Saake, Gunter ED - Meinel, Christoph ED - Polze, Andreas ED - Beins, Karsten ED - Strotmann, Rolf ED - Seibold, Ulrich ED - Rödszus, Kurt ED - Müller, Jürgen T1 - HPI Future SOC Lab – Proceedings 2019 N2 - The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners. The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies. This technical report presents results of research projects executed in 2019. Selected projects have presented their results on April 9th and November 12th 2019 at the Future SOC Lab Day events. N2 - Das Future SOC Lab am HPI ist eine Kooperation des Hasso-Plattner-Instituts mit verschiedenen Industriepartnern. Seine Aufgabe ist die Ermöglichung und Förderung des Austausches zwischen Forschungsgemeinschaft und Industrie. Am Lab wird interessierten Wissenschaftlern eine Infrastruktur von neuester Hard- und Software kostenfrei für Forschungszwecke zur Verfügung gestellt. Dazu zählen teilweise noch nicht am Markt verfügbare Technologien, die im normalen Hochschulbereich in der Regel nicht zu finanzieren wären, bspw. Server mit bis zu 64 Cores und 2 TB Hauptspeicher. Diese Angebote richten sich insbesondere an Wissenschaftler in den Gebieten Informatik und Wirtschaftsinformatik. Einige der Schwerpunkte sind Cloud Computing, Parallelisierung und In-Memory Technologien. In diesem Technischen Bericht werden die Ergebnisse der Forschungsprojekte des Jahres 2019 vorgestellt. Ausgewählte Projekte stellten ihre Ergebnisse am 09. April und 12. November 2019 im Rahmen des Future SOC Lab Tags vor. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 158 KW - Future SOC Lab KW - research projects KW - multicore architectures KW - in-memory technology KW - cloud computing KW - machine learning KW - artifical intelligence KW - Future SOC Lab KW - Forschungsprojekte KW - Multicore Architekturen KW - In-Memory Technologie KW - Cloud Computing KW - maschinelles Lernen KW - künstliche Intelligenz Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-597915 SN - 978-3-86956-564-4 SN - 1613-5652 SN - 2191-1665 IS - 158 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - THES A1 - Richly, Keven T1 - Memory-efficient data management for spatio-temporal applications BT - workload-driven fine-grained configuration optimization for storing spatio-temporal data in columnar In-memory databases N2 - The wide distribution of location-acquisition technologies means that large volumes of spatio-temporal data are continuously being accumulated. Positioning systems such as GPS enable the tracking of various moving objects' trajectories, which are usually represented by a chronologically ordered sequence of observed locations. The analysis of movement patterns based on detailed positional information creates opportunities for applications that can improve business decisions and processes in a broad spectrum of industries (e.g., transportation, traffic control, or medicine). Due to the large data volumes generated in these applications, the cost-efficient storage of spatio-temporal data is desirable, especially when in-memory database systems are used to achieve interactive performance requirements. To efficiently utilize the available DRAM capacities, modern database systems support various tuning possibilities to reduce the memory footprint (e.g., data compression) or increase performance (e.g., additional indexes structures). By considering horizontal data partitioning, we can independently apply different tuning options on a fine-grained level. However, the selection of cost and performance-balancing configurations is challenging, due to the vast number of possible setups consisting of mutually dependent individual decisions. In this thesis, we introduce multiple approaches to improve spatio-temporal data management by automatically optimizing diverse tuning options for the application-specific access patterns and data characteristics. Our contributions are as follows: (1) We introduce a novel approach to determine fine-grained table configurations for spatio-temporal workloads. Our linear programming (LP) approach jointly optimizes the (i) data compression, (ii) ordering, (iii) indexing, and (iv) tiering. We propose different models which address cost dependencies at different levels of accuracy to compute optimized tuning configurations for a given workload, memory budgets, and data characteristics. To yield maintainable and robust configurations, we further extend our LP-based approach to incorporate reconfiguration costs as well as optimizations for multiple potential workload scenarios. (2) To optimize the storage layout of timestamps in columnar databases, we present a heuristic approach for the workload-driven combined selection of a data layout and compression scheme. By considering attribute decomposition strategies, we are able to apply application-specific optimizations that reduce the memory footprint and improve performance. (3) We introduce an approach that leverages past trajectory data to improve the dispatch processes of transportation network companies. Based on location probabilities, we developed risk-averse dispatch strategies that reduce critical delays. (4) Finally, we used the use case of a transportation network company to evaluate our database optimizations on a real-world dataset. We demonstrate that workload-driven fine-grained optimizations allow us to reduce the memory footprint (up to 71% by equal performance) or increase the performance (up to 90% by equal memory size) compared to established rule-based heuristics. Individually, our contributions provide novel approaches to the current challenges in spatio-temporal data mining and database research. Combining them allows in-memory databases to store and process spatio-temporal data more cost-efficiently. N2 - Durch die starke Verbreitung von Systemen zur Positionsbestimmung werden fortlaufend große Mengen an Bewegungsdaten mit einem räumlichen und zeitlichen Bezug gesammelt. Ortungssysteme wie GPS ermöglichen, die Bewegungen verschiedener Objekte (z. B. Personen oder Fahrzeuge) nachzuverfolgen. Diese werden in der Regel durch eine chronologisch geordnete Abfolge beobachteter Aufenthaltsorte repräsentiert. Die Analyse von Bewegungsmustern auf der Grundlage detaillierter Positionsinformationen schafft in unterschiedlichsten Branchen (z. B. Transportwesen, Verkehrssteuerung oder Medizin) die Möglichkeit Geschäftsentscheidungen und -prozesse zu verbessern. Aufgrund der großen Datenmengen, die bei diesen Anwendungen auftreten, stellt die kosteneffiziente Speicherung von Bewegungsdaten eine Herausforderung dar. Dies ist insbesondere der Fall, wenn Hauptspeicherdatenbanken zur Speicherung eingesetzt werden, um die Anforderungen bezüglich interaktiver Antwortzeiten zu erfüllen. Um die verfügbaren Speicherkapazitäten effizient zu nutzen, unterstützen moderne Datenbanksysteme verschiedene Optimierungsmöglichkeiten, um den Speicherbedarf zu reduzieren (z. B. durch Datenkomprimierung) oder die Performance zu erhöhen (z. B. durch Indexstrukturen). Dabei ermöglicht eine horizontale Partitionierung der Daten, dass unabhängig voneinander verschiedene Optimierungen feingranular auf einzelnen Bereichen der Daten angewendet werden können. Die Auswahl von Konfigurationen, die sowohl die Kosten als auch Leistungsanforderungen berücksichtigen, ist jedoch aufgrund der großen Anzahl möglicher Kombinationen -- die aus voneinander abhängigen Einzelentscheidungen bestehen -- komplex. In dieser Dissertation präsentieren wir mehrere Ansätze zur Verbesserung der Datenverwaltung, indem wir die Auswahl verschiedener Datenbankoptimierungen automatisch für die anwendungsspezifischen Zugriffsmuster und Dateneigenschaften anpassen. Diesbezüglich leistet die vorliegende Dissertation die folgenden Beiträge: (1) Wir stellen einen neuen Ansatz vor, um feingranulare Tabellenkonfigurationen für räumlich-zeitliche Workloads zu bestimmen. In diesem Zusammenhang optimiert unser Linear Programming (LP) Ansatz gemeinsam (i) die Datenkompression, (ii) die Sortierung, (iii) die Indizierung und (iv) die Datenplatzierung. Hierzu schlagen wir verschiedene Modelle mit unterschiedlichen Kostenabhängigkeiten vor, um optimierte Konfigurationen für einen gegebenen Workload, ein Speicherbudget und die vorliegenden Dateneigenschaften zu berechnen. Durch die Erweiterung des LP-basierten Ansatzes zur Berücksichtigung von Modifikationskosten und verschiedener potentieller Workloads ist es möglich, die Wartbarkeit und Robustheit der bestimmten Tabellenkonfiguration zu erhöhen. (2) Um die Speicherung von Timestamps in spalten-orientierten Datenbanken zu optimieren, stellen wir einen heuristischen Ansatz für die kombinierte Auswahl eines Speicherlayouts und eines Kompressionsschemas vor. Zudem sind wir durch die Berücksichtigung von Strategien zur Aufteilung von Attributen in der Lage, anwendungsspezifische Optimierungen anzuwenden, die den Speicherbedarf reduzieren und die Performance verbessern. (3) Wir stellen einen Ansatz vor, der in der Vergangenheit beobachtete Bewegungsmuster nutzt, um die Zuweisungsprozesse von Vermittlungsdiensten zur Personenbeförderung zu verbessern. Auf der Grundlage von Standortwahrscheinlichkeiten haben wir verschiedene Strategien für die Vergabe von Fahraufträgen an Fahrer entwickelt, die kritische Verspätungen reduzieren. (4) Abschließend haben wir unsere Datenbankoptimierungen anhand eines realen Datensatzes eines Transportdienstleisters evaluiert. In diesem Zusammenhang zeigen wir, dass wir durch feingranulare workload-basierte Optimierungen den Speicherbedarf (um bis zu 71% bei vergleichbarer Performance) reduzieren oder die Performance (um bis zu 90% bei gleichem Speicherverbrauch) im Vergleich zu regelbasierten Heuristiken verbessern können. Die einzelnen Beiträge stellen neuartige Ansätze für aktuelle Herausforderungen im Bereich des Data Mining und der Datenbankforschung dar. In Kombination ermöglichen sie eine kosteneffizientere Speicherung und Verarbeitung von Bewegungsdaten in Hauptspeicherdatenbanken. KW - spatio-temporal data management KW - trajectory data KW - columnar databases KW - in-memory data management KW - database tuning KW - spaltenorientierte Datenbanken KW - Datenbankoptimierung KW - Hauptspeicher Datenmanagement KW - Datenverwaltung für Daten mit räumlich-zeitlichem Bezug KW - Trajektoriendaten Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-635473 ER - TY - JOUR A1 - Ring, Raphaela M. A1 - Eisenmann, Clemens A1 - Kandil, Farid A1 - Steckhan, Nico A1 - Demmrich, Sarah A1 - Klatte, Caroline A1 - Kessler, Christian S. A1 - Jeitler, Michael A1 - Boschmann, Michael A1 - Michalsen, Andreas A1 - Blakeslee, Sarah B. A1 - Stöckigt, Barbara A1 - Stritter, Wiebke A1 - Koppold-Liebscher, Daniela A. T1 - Mental and behavioural responses to Bahá’í fasting: Looking behind the scenes of a religiously motivated intermittent fast using a mixed methods approach JF - Nutrients N2 - Background/Objective: Historically, fasting has been practiced not only for medical but also for religious reasons. Baha'is follow an annual religious intermittent dry fast of 19 days. We inquired into motivation behind and subjective health impacts of Baha'i fasting. Methods: A convergent parallel mixed methods design was embedded in a clinical single arm observational study. Semi-structured individual interviews were conducted before (n = 7), during (n = 8), and after fasting (n = 8). Three months after the fasting period, two focus group interviews were conducted (n = 5/n = 3). A total of 146 Baha'i volunteers answered an online survey at five time points before, during, and after fasting. Results: Fasting was found to play a central role for the religiosity of interviewees, implying changes in daily structures, spending time alone, engaging in religious practices, and experiencing social belonging. Results show an increase in mindfulness and well-being, which were accompanied by behavioural changes and experiences of self-efficacy and inner freedom. Survey scores point to an increase in mindfulness and well-being during fasting, while stress, anxiety, and fatigue decreased. Mindfulness remained elevated even three months after the fast. Conclusion: Baha'i fasting seems to enhance participants' mindfulness and well-being, lowering stress levels and reducing fatigue. Some of these effects lasted more than three months after fasting. KW - intermittent food restriction KW - mindfulness KW - self-efficacy KW - well-being KW - mixed methods KW - health behaviour KW - coping ability KW - religiously motivated KW - dry fasting Y1 - 2022 U6 - https://doi.org/10.3390/nu14051038 SN - 2072-6643 VL - 14 IS - 5 PB - MDPI CY - Basel ER - TY - BOOK A1 - Meinel, Christoph A1 - Döllner, Jürgen Roland Friedrich A1 - Weske, Mathias A1 - Polze, Andreas A1 - Hirschfeld, Robert A1 - Naumann, Felix A1 - Giese, Holger A1 - Baudisch, Patrick A1 - Friedrich, Tobias A1 - Böttinger, Erwin A1 - Lippert, Christoph A1 - Dörr, Christian A1 - Lehmann, Anja A1 - Renard, Bernhard A1 - Rabl, Tilmann A1 - Uebernickel, Falk A1 - Arnrich, Bert A1 - Hölzle, Katharina T1 - Proceedings of the HPI Research School on Service-oriented Systems Engineering 2020 Fall Retreat N2 - Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application. Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns. The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment. N2 - Der Entwurf und die Realisierung dienstbasierender Architekturen wirft eine Vielzahl von Forschungsfragestellungen aus den Gebieten der Softwaretechnik, der Systemmodellierung und -analyse, sowie der Adaptierbarkeit und Integration von Applikationen auf. Komponentenorientierung und WebServices sind zwei Ansätze für den effizienten Entwurf und die Realisierung komplexer Web-basierender Systeme. Sie ermöglichen die Reaktion auf wechselnde Anforderungen ebenso, wie die Integration großer komplexer Softwaresysteme. "Service-Oriented Systems Engineering" repräsentiert die Symbiose bewährter Praktiken aus den Gebieten der Objektorientierung, der Komponentenprogrammierung, des verteilten Rechnen sowie der Geschäftsprozesse und berücksichtigt auch die Integration von Geschäftsanliegen und Informationstechnologien. Die Klausurtagung des Forschungskollegs "Service-oriented Systems Engineering" findet einmal jährlich statt und bietet allen Kollegiaten die Möglichkeit den Stand ihrer aktuellen Forschung darzulegen. Bedingt durch die Querschnittstruktur des Kollegs deckt dieser Bericht ein weites Spektrum aktueller Forschungsthemen ab. Dazu zählen unter anderem Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; sowie Services Specification, Composition, and Enactment. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 138 KW - Hasso Plattner Institute KW - research school KW - Ph.D. retreat KW - service-oriented systems engineering KW - Hasso-Plattner-Institut KW - Forschungskolleg KW - Klausurtagung KW - Service-oriented Systems Engineering Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-504132 SN - 978-3-86956-513-2 SN - 1613-5652 SN - 2191-1665 IS - 138 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Lewkowicz, Daniel A1 - Wohlbrandt, Attila A1 - Böttinger, Erwin T1 - Economic impact of clinical decision support interventions based on electronic health records T2 - Postprints der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Background Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on electronic health records (EHR). Methods We searched for studies published after 2014 using MEDLINE, CENTRAL, WEB OF SCIENCE, EBSCO, and TUFTS CEA registry databases that encompass an economic evaluation or consider cost outcome measures of EHR based CDS interventions. Thereupon, we identified best practice application areas and categorized the investigated interventions according to an existing taxonomy of front-end CDS tools. Results and discussion Twenty-seven studies are investigated in this review. Of those, twenty-two studies indicate a reduction of healthcare expenditure after implementing an EHR based CDS system, especially towards prevalent application areas, such as unnecessary laboratory testing, duplicate order entry, efficient transfusion practice, or reduction of antibiotic prescriptions. On the contrary, order facilitators and undiscovered malfunctions revealed to be threats and could lead to new cost drivers in healthcare. While high upfront and maintenance costs of CDS systems are a worldwide implementation barrier, most studies do not consider implementation cost. Finally, four included economic evaluation studies report mixed monetary outcome results and thus highlight the importance of further high-quality economic evaluations for these CDS systems. Conclusion Current research studies lack consideration of comparative cost-outcome metrics as well as detailed cost components in their analyses. Nonetheless, the positive economic impact of EHR based CDS interventions is highly promising, especially with regard to reducing waste in healthcare. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 5 KW - Economic evaluation KW - Electronic health record KW - Clinical decision support KW - Behavioral economics Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-501376 IS - 5 ER - TY - JOUR A1 - Lewkowicz, Daniel A1 - Wohlbrandt, Attila A1 - Böttinger, Erwin T1 - Economic impact of clinical decision support interventions based on electronic health records JF - BMC Health Services Research N2 - Background Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on electronic health records (EHR). Methods We searched for studies published after 2014 using MEDLINE, CENTRAL, WEB OF SCIENCE, EBSCO, and TUFTS CEA registry databases that encompass an economic evaluation or consider cost outcome measures of EHR based CDS interventions. Thereupon, we identified best practice application areas and categorized the investigated interventions according to an existing taxonomy of front-end CDS tools. Results and discussion Twenty-seven studies are investigated in this review. Of those, twenty-two studies indicate a reduction of healthcare expenditure after implementing an EHR based CDS system, especially towards prevalent application areas, such as unnecessary laboratory testing, duplicate order entry, efficient transfusion practice, or reduction of antibiotic prescriptions. On the contrary, order facilitators and undiscovered malfunctions revealed to be threats and could lead to new cost drivers in healthcare. While high upfront and maintenance costs of CDS systems are a worldwide implementation barrier, most studies do not consider implementation cost. Finally, four included economic evaluation studies report mixed monetary outcome results and thus highlight the importance of further high-quality economic evaluations for these CDS systems. Conclusion Current research studies lack consideration of comparative cost-outcome metrics as well as detailed cost components in their analyses. Nonetheless, the positive economic impact of EHR based CDS interventions is highly promising, especially with regard to reducing waste in healthcare. KW - Economic evaluation KW - Electronic health record KW - Clinical decision support KW - Behavioral economics Y1 - 2020 U6 - https://doi.org/10.1186/s12913-020-05688-3 SN - 1472-6963 VL - 20 PB - BioMed Central CY - London ER - TY - GEN A1 - Gorski, Mathias A1 - Jung, Bettina A1 - Li, Yong A1 - Matias-Garcia, Pamela R. A1 - Wuttke, Matthias A1 - Coassin, Stefan A1 - Thio, Chris H. L. A1 - Kleber, Marcus E. A1 - Winkler, Thomas W. A1 - Wanner, Veronika A1 - Chai, Jin-Fang A1 - Chu, Audrey Y. A1 - Cocca, Massimiliano A1 - Feitosa, Mary F. A1 - Ghasemi, Sahar A1 - Hoppmann, Anselm A1 - Horn, Katrin A1 - Li, Man A1 - Nutile, Teresa A1 - Scholz, Markus A1 - Sieber, Karsten B. A1 - Teumer, Alexander A1 - Tin, Adrienne A1 - Wang, Judy A1 - Tayo, Bamidele O. A1 - Ahluwalia, Tarunveer S. A1 - Almgren, Peter A1 - Bakker, Stephan J. L. A1 - Banas, Bernhard A1 - Bansal, Nisha A1 - Biggs, Mary L. A1 - Boerwinkle, Eric A1 - Böttinger, Erwin A1 - Brenner, Hermann A1 - Carroll, Robert J. A1 - Chalmers, John A1 - Chee, Miao-Li A1 - Chee, Miao-Ling A1 - Cheng, Ching-Yu A1 - Coresh, Josef A1 - de Borst, Martin H. A1 - Degenhardt, Frauke A1 - Eckardt, Kai-Uwe A1 - Endlich, Karlhans A1 - Franke, Andre A1 - Freitag-Wolf, Sandra A1 - Gampawar, Piyush A1 - Gansevoort, Ron T. A1 - Ghanbari, Mohsen A1 - Gieger, Christian A1 - Hamet, Pavel A1 - Ho, Kevin A1 - Hofer, Edith A1 - Holleczek, Bernd A1 - Foo, Valencia Hui Xian A1 - Hutri-Kahonen, Nina A1 - Hwang, Shih-Jen A1 - Ikram, M. Arfan A1 - Josyula, Navya Shilpa A1 - Kahonen, Mika A1 - Khor, Chiea-Chuen A1 - Koenig, Wolfgang A1 - Kramer, Holly A1 - Kraemer, Bernhard K. A1 - Kuehnel, Brigitte A1 - Lange, Leslie A. A1 - Lehtimaki, Terho A1 - Lieb, Wolfgang A1 - Loos, Ruth J. F. A1 - Lukas, Mary Ann A1 - Lyytikainen, Leo-Pekka A1 - Meisinger, Christa A1 - Meitinger, Thomas A1 - Melander, Olle A1 - Milaneschi, Yuri A1 - Mishra, Pashupati P. A1 - Mononen, Nina A1 - Mychaleckyj, Josyf C. A1 - Nadkarni, Girish N. A1 - Nauck, Matthias A1 - Nikus, Kjell A1 - Ning, Boting A1 - Nolte, Ilja M. A1 - O'Donoghue, Michelle L. A1 - Orho-Melander, Marju A1 - Pendergrass, Sarah A. A1 - Penninx, Brenda W. J. H. A1 - Preuss, Michael H. A1 - Psaty, Bruce M. A1 - Raffield, Laura M. A1 - Raitakari, Olli T. A1 - Rettig, Rainer A1 - Rheinberger, Myriam A1 - Rice, Kenneth M. A1 - Rosenkranz, Alexander R. A1 - Rossing, Peter A1 - Rotter, Jerome A1 - Sabanayagam, Charumathi A1 - Schmidt, Helena A1 - Schmidt, Reinhold A1 - Schoettker, Ben A1 - Schulz, Christina-Alexandra A1 - Sedaghat, Sanaz A1 - Shaffer, Christian M. A1 - Strauch, Konstantin A1 - Szymczak, Silke A1 - Taylor, Kent D. A1 - Tremblay, Johanne A1 - Chaker, Layal A1 - van der Harst, Pim A1 - van der Most, Peter J. A1 - Verweij, Niek A1 - Voelker, Uwe A1 - Waldenberger, Melanie A1 - Wallentin, Lars A1 - Waterworth, Dawn M. A1 - White, Harvey D. A1 - Wilson, James G. A1 - Wong, Tien-Yin A1 - Woodward, Mark A1 - Yang, Qiong A1 - Yasuda, Masayuki A1 - Yerges-Armstrong, Laura M. A1 - Zhang, Yan A1 - Snieder, Harold A1 - Wanner, Christoph A1 - Boger, Carsten A. A1 - Kottgen, Anna A1 - Kronenberg, Florian A1 - Pattaro, Cristian A1 - Heid, Iris M. T1 - Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m(2)/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m(2) at follow-up among those with eGFRcrea 60 mL/min/1.73m(2) or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or (LARP4B). Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 19 KW - acute kidney injury KW - end-stage kidney disease KW - genome-wide association KW - study KW - rapid eGFRcrea decline Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-565379 IS - 19 ER - TY - GEN A1 - Perscheid, Cindy A1 - Faber, Lukas A1 - Kraus, Milena A1 - Arndt, Paul A1 - Janke, Michael A1 - Rehfeldt, Sebastian A1 - Schubotz, Antje A1 - Slosarek, Tamara A1 - Uflacker, Matthias T1 - A tissue-aware gene selection approach for analyzing multi-tissue gene expression data T2 - 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) N2 - High-throughput RNA sequencing (RNAseq) produces large data sets containing expression levels of thousands of genes. The analysis of RNAseq data leads to a better understanding of gene functions and interactions, which eventually helps to study diseases like cancer and develop effective treatments. Large-scale RNAseq expression studies on cancer comprise samples from multiple cancer types and aim to identify their distinct molecular characteristics. Analyzing samples from different cancer types implies analyzing samples from different tissue origin. Such multi-tissue RNAseq data sets require a meaningful analysis that accounts for the inherent tissue-related bias: The identified characteristics must not originate from the differences in tissue types, but from the actual differences in cancer types. However, current analysis procedures do not incorporate that aspect. As a result, we propose to integrate a tissue-awareness into the analysis of multi-tissue RNAseq data. We introduce an extension for gene selection that provides a tissue-wise context for every gene and can be flexibly combined with any existing gene selection approach. We suggest to expand conventional evaluation by additional metrics that are sensitive to the tissue-related bias. Evaluations show that especially low complexity gene selection approaches profit from introducing tissue-awareness. KW - RNAseq KW - gene selection KW - tissue-awareness KW - TCGA KW - GTEx Y1 - 2018 SN - 978-1-5386-5488-0 U6 - https://doi.org/10.1109/BIBM.2018.8621189 SN - 2156-1125 SN - 2156-1133 SP - 2159 EP - 2166 PB - IEEE CY - New York ER - TY - GEN A1 - Horowitz, Carol R. A1 - Fei, Kezhen A1 - Ramos, Michelle A. A1 - Hauser, Diane A1 - Ellis, Stephen B. A1 - Calman, Neil A1 - Böttinger, Erwin T1 - Receipt of genetic risk information significantly improves blood pressure control among African anecestry adults with hypertension BT - results of a randomized trail T2 - Journal of General Internal Medicine Y1 - 2018 U6 - https://doi.org/10.1007/s11606-018-4413-y SN - 0884-8734 SN - 1525-1497 VL - 33 SP - S322 EP - S323 PB - Springer CY - New York ER - TY - GEN A1 - Zenner, Alexander M. A1 - Böttinger, Erwin A1 - Konigorski, Stefan T1 - StudyMe BT - a new mobile app for user-centric N-of-1 trials T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 18 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-589763 IS - 18 ER - TY - JOUR A1 - Zenner, Alexander M. A1 - Böttinger, Erwin A1 - Konigorski, Stefan T1 - StudyMe BT - a new mobile app for user-centric N-of-1 trials JF - Trials N2 - N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives. Y1 - 2022 U6 - https://doi.org/10.1186/s13063-022-06893-7 SN - 1745-6215 VL - 23 PB - BioMed Central CY - London ER - TY - THES A1 - Kraus, Sara Milena T1 - A Systems Medicine approach for heart valve diseases BT - addressing the proteomic landscape and differential expression software N2 - In Systems Medicine, in addition to high-throughput molecular data (*omics), the wealth of clinical characterization plays a major role in the overall understanding of a disease. Unique problems and challenges arise from the heterogeneity of data and require new solutions to software and analysis methods. The SMART and EurValve studies establish a Systems Medicine approach to valvular heart disease -- the primary cause of subsequent heart failure. With the aim to ascertain a holistic understanding, different *omics as well as the clinical picture of patients with aortic stenosis (AS) and mitral regurgitation (MR) are collected. Our task within the SMART consortium was to develop an IT platform for Systems Medicine as a basis for data storage, processing, and analysis as a prerequisite for collaborative research. Based on this platform, this thesis deals on the one hand with the transfer of the used Systems Biology methods to their use in the Systems Medicine context and on the other hand with the clinical and biomolecular differences of the two heart valve diseases. To advance differential expression/abundance (DE/DA) analysis software for use in Systems Medicine, we state 21 general software requirements and features of automated DE/DA software, including a novel concept for the simple formulation of experimental designs that can represent complex hypotheses, such as comparison of multiple experimental groups, and demonstrate our handling of the wealth of clinical data in two research applications DEAME and Eatomics. In user interviews, we show that novice users are empowered to formulate and test their multiple DE hypotheses based on clinical phenotype. Furthermore, we describe insights into users' general impression and expectation of the software's performance and show their intention to continue using the software for their work in the future. Both research applications cover most of the features of existing tools or even extend them, especially with respect to complex experimental designs. Eatomics is freely available to the research community as a user-friendly R Shiny application. Eatomics continued to help drive the collaborative analysis and interpretation of the proteomic profile of 75 human left myocardial tissue samples from the SMART and EurValve studies. Here, we investigate molecular changes within the two most common types of valvular heart disease: aortic valve stenosis (AS) and mitral valve regurgitation (MR). Through DE/DA analyses, we explore shared and disease-specific protein alterations, particularly signatures that could only be found in the sex-stratified analysis. In addition, we relate changes in the myocardial proteome to parameters from clinical imaging. We find comparable cardiac hypertrophy but differences in ventricular size, the extent of fibrosis, and cardiac function. We find that AS and MR show many shared remodeling effects, the most prominent of which is an increase in the extracellular matrix and a decrease in metabolism. Both effects are stronger in AS. In muscle and cytoskeletal adaptations, we see a greater increase in mechanotransduction in AS and an increase in cortical cytoskeleton in MR. The decrease in proteostasis proteins is mainly attributable to the signature of female patients with AS. We also find relevant therapeutic targets. In addition to the new findings, our work confirms several concepts from animal and heart failure studies by providing the largest collection of human tissue from in vivo collected biopsies to date. Our dataset contributing a resource for isoform-specific protein expression in two of the most common valvular heart diseases. Apart from the general proteomic landscape, we demonstrate the added value of the dataset by showing proteomic and transcriptomic evidence for increased expression of the SARS-CoV-2- receptor at pressure load but not at volume load in the left ventricle and also provide the basis of a newly developed metabolic model of the heart. N2 - In der Systemmedizin spielt zusätzlich zu den molekularen Hochdurchsatzdaten (*omics) die Fülle an klinischer Charakterisierung eine große Rolle im Gesamtverständnis einer Krankheit. Hieraus ergeben sich Probleme und Herausforderungen unter anderem in Bezug auf Softwarelösungen und Analysemethoden. Die SMART- und EurValve-Studien etablieren einen systemmedizinischen Ansatz für Herzklappenerkrankungen -- die Hauptursache für eine spätere Herzinsuffizienz. Mit dem Ziel ein ganzheitliches Verständnis zu etablieren, werden verschiedene *omics sowie das klinische Bild von Patienten mit Aortenstenosen (AS) und Mitralklappeninsuffizienz (MR) erhoben. Unsere Aufgabe innerhalb des SMART Konsortiums bestand in der Entwicklung einer IT-Plattform für Systemmedizin als Grundlage für die Speicherung, Verarbeitung und Analyse von Daten als Voraussetzung für gemeinsame Forschung. Ausgehend von dieser Plattform beschäftigt sich diese Arbeit einerseits mit dem Transfer der genutzten systembiologischen Methoden hin zu einer Nutzung im systemmedizinischen Kontext und andererseits mit den klinischen und biomolekularen Unterschieden der beiden Herzklappenerkrankungen. Um die Analysesoftware für differenzielle Expression/Abundanz, eine häufig genutzte Methode der System Biologie, für die Nutzung in der Systemmedizin voranzutreiben, erarbeiten wir 21 allgemeine Softwareanforderungen und Funktionen einer automatisierten DE/DA Software. Darunter ist ein neuartiges Konzept für die einfache Formulierung experimenteller Designs, die auch komplexe Hypothesen wie den Vergleich mehrerer experimenteller Gruppen abbilden können und demonstrieren unseren Umgang mit der Fülle klinischer Daten in zwei Forschungsanwendungen -- DEAME und Eatomics. In Nutzertests zeigen wir, dass Nutzer befähigt werden, ihre vielfältigen Hypothesen zur differenziellen Expression basierend auf dem klinischen Phänotyp zu formulieren und zu testen, auch ohne einen dedizierten Hintergrund in Bioinformatik. Darüber hinaus beschreiben wir Einblicke in den allgemeinen Eindruck der Nutzer, ihrer Erwartung an die Leistung der Software und zeigen ihre Absicht, die Software auch in der Zukunft für ihre Arbeit zu nutzen. Beide Forschungsanwendungen decken die meisten Funktionen bestehender Tools ab oder erweitern sie sogar, insbesondere im Hinblick auf komplexe experimentelle Designs. Eatomics steht der Forschungsgemeinschaft als benutzerfreundliche R Shiny-Anwendung frei zur Verfügung. \textit{Eatomics} hat weiterhin dazu beigetragen, die gemeinsame Analyse und Interpretation des Proteomprofils von 75 menschlichen linken Myokardgewebeproben aus den SMART- und EurValve-Studien voran zu treiben. Hier untersuchen wir die molekularen Veränderungen innerhalb der beiden häufigsten Arten von Herzklappenerkrankungen: AS und MR. Durch DE/DA Analysen erarbeiten wir gemeinsame und krankheitsspezifische Proteinveränderungen, insbesondere Signaturen, die nur in einer geschlechtsstratifizierten Analyse gefunden werden konnten. Darüber hinaus beziehen wir Veränderungen des Myokardproteoms auf Parameter aus der klinischen Bildgebung. Wir finden eine vergleichbare kardiale Hypertrophie, aber Unterschiede in der Ventrikelgröße, dem Ausmaß der Fibrose und der kardialen Funktion. Wir stellen fest, dass AS und MR viele gemeinsame Remodelling-Effekte zeigen, von denen die wichtigsten die Zunahme der extrazellulären Matrix und eine Abnahme des Metabolismus sind. Beide Effekte sind bei AS stärker. Zusätzlich zeigt sich eine größere Variabilität zwischen den einzelnen Patienten mit AS. Bei Muskel- und Zytoskelettanpassungen sehen wir einen stärkeren Anstieg der Mechanotransduktion bei AS und einen Anstieg des kortikalen Zytoskeletts bei MR. Die Abnahme von Proteinen der Proteostase ist vor allem der Signatur von weiblichen Patienten mit AS zuzuschreiben. Außerdem finden wir therapierelevante Proteinveränderungen. Zusätzlich zu den neuen Erkenntnissen bestätigt unsere Arbeit mehrere Konzepte aus Tierstudien und Studien zu Herzversagen durch die bislang größte Kollektion von humanem Gewebe aus in vivo Biopsien. Mit unserem Datensatz stellen wir eine Ressource für die isoformspezifische Proteinexpression bei zwei der häufigsten Herzklappenerkrankungen zur Verfügung. Abgesehen von der allgemeinen Proteomlandschaft zeigen wir den Mehrwert des Datensatzes, indem wir proteomische und transkriptomische Beweise für eine erhöhte Expression des SARS-CoV-2- Rezeptors bei Drucklast, jedoch nicht bei Volumenlast im linken Ventrikel aufzeigen und außerdem die Grundlage eines neu entwickelten metabolischen Modells des Herzens liefern. KW - Systems Medicine KW - Systemmedizin KW - Proteomics KW - Proteom KW - Heart Valve Diseases KW - Herzklappenerkrankungen KW - Differential Expression Analysis KW - Software KW - Software Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-522266 ER - TY - JOUR A1 - Lewkowicz, Daniel A1 - Böttinger, Erwin A1 - Siegel, Martin T1 - Economic evaluation of digital therapeutic care apps for unsupervised treatment of low back pain BT - Monte Carlo Simulation JF - JMIR mhealth and uhealth N2 - Background: Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany. Objective: The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results. Methods: The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany. Results: The Monte Carlo simulation yielded on average a euro135.97 (a currency exchange rate of EUR euro1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional euro34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently euro239.96 to euro164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%. Conclusions: Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps. KW - cost-utility analysis KW - cost KW - probabilistic sensitivity analysis KW - Monte Carlo simulation KW - low back pain KW - pain KW - economic KW - cost-effectiveness KW - Markov model KW - digital therapy KW - digital health app KW - mHealth KW - mobile health KW - health app KW - mobile app KW - orthopedic KW - QUALY KW - DALY KW - quality-adjusted life years KW - disability-adjusted life years KW - time horizon KW - veteran KW - statistics Y1 - 2023 U6 - https://doi.org/10.2196/44585 SN - 2291-5222 VL - 11 PB - JMIR Publications CY - Toronto ER - TY - JOUR A1 - Rüther, Ferenc Darius A1 - Sebode, Marcial A1 - Lohse, Ansgar W. A1 - Wernicke, Sarah A1 - Böttinger, Erwin A1 - Casar, Christian A1 - Braun, Felix A1 - Schramm, Christoph T1 - Mobile app requirements for patients with rare liver diseases BT - a single center survey for the ERN RARE-LIVER JF - Clinics and research in hepatology and gastroenterology N2 - Background: More patient data are needed to improve research on rare liver diseases. Mobile health apps enable an exhaustive data collection. Therefore, the European Reference Network on Hepatological diseases (ERN RARE-LIVER) intends to implement an app for patients with rare liver diseases communicating with a patient registry, but little is known about which features patients and their healthcare providers regard as being useful. Aims: This study aimed to investigate how an app for rare liver diseases would be accepted, and to find out which features are considered useful. Methods: An anonymous survey was conducted on adult patients with rare liver diseases at a single academic, tertiary care outpatient-service. Additionally, medical experts of the ERN working group on autoimmune hepatitis were invited to participate in an online survey. Results: In total, the responses from 100 patients with autoimmune (n = 90) or other rare (n = 10) liver diseases and 32 experts were analyzed. Patients were convinced to use a disease specific app (80%) and expected some benefit to their health (78%) but responses differed signifi-cantly between younger and older patients (93% vs. 62%, p < 0.001; 88% vs. 64%, p < 0.01). Comparing patients' and experts' feedback, patients more often expected a simplified healthcare pathway (e.g. 89% vs. 59% (p < 0.001) wanted access to one's own medical records), while healthcare providers saw the benefit mainly in improving compliance and treatment outcome (e.g. 93% vs. 31% (p < 0.001) and 70% vs. 21% (p < 0.001) expected the app to reduce mistakes in taking medication and improve quality of life, respectively). KW - Primary sclerosing cholangitis KW - Primary biliary cholangitis KW - Autoimmune KW - hepatitis KW - European reference networks KW - Mobile applications KW - Patient KW - reported out-come measures Y1 - 2021 U6 - https://doi.org/10.1016/j.clinre.2021.101760 SN - 2210-7401 SN - 2210-741X VL - 45 IS - 6 PB - Elsevier Masson CY - Amsterdam ER - TY - JOUR A1 - Freitas da Cruz, Harry A1 - Pfahringer, Boris A1 - Martensen, Tom A1 - Schneider, Frederic A1 - Meyer, Alexander A1 - Böttinger, Erwin A1 - Schapranow, Matthieu-Patrick T1 - Using interpretability approaches to update "black-box" clinical prediction models BT - an external validation study in nephrology JF - Artificial intelligence in medicine : AIM N2 - Despite advances in machine learning-based clinical prediction models, only few of such models are actually deployed in clinical contexts. Among other reasons, this is due to a lack of validation studies. In this paper, we present and discuss the validation results of a machine learning model for the prediction of acute kidney injury in cardiac surgery patients initially developed on the MIMIC-III dataset when applied to an external cohort of an American research hospital. To help account for the performance differences observed, we utilized interpretability methods based on feature importance, which allowed experts to scrutinize model behavior both at the global and local level, making it possible to gain further insights into why it did not behave as expected on the validation cohort. The knowledge gleaned upon derivation can be potentially useful to assist model update during validation for more generalizable and simpler models. We argue that interpretability methods should be considered by practitioners as a further tool to help explain performance differences and inform model update in validation studies. KW - Clinical predictive modeling KW - Nephrology KW - Validation KW - Interpretability KW - methods Y1 - 2021 U6 - https://doi.org/10.1016/j.artmed.2020.101982 SN - 0933-3657 SN - 1873-2860 VL - 111 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Wuttke, Matthias A1 - Li, Yong A1 - Li, Man A1 - Sieber, Karsten B. A1 - Feitosa, Mary F. A1 - Gorski, Mathias A1 - Tin, Adrienne A1 - Wang, Lihua A1 - Chu, Audrey Y. A1 - Hoppmann, Anselm A1 - Kirsten, Holger A1 - Giri, Ayush A1 - Chai, Jin-Fang A1 - Sveinbjornsson, Gardar A1 - Tayo, Bamidele O. A1 - Nutile, Teresa A1 - Fuchsberger, Christian A1 - Marten, Jonathan A1 - Cocca, Massimiliano A1 - Ghasemi, Sahar A1 - Xu, Yizhe A1 - Horn, Katrin A1 - Noce, Damia A1 - Van der Most, Peter J. A1 - Sedaghat, Sanaz A1 - Yu, Zhi A1 - Akiyama, Masato A1 - Afaq, Saima A1 - Ahluwalia, Tarunveer Singh A1 - Almgren, Peter A1 - Amin, Najaf A1 - Arnlov, Johan A1 - Bakker, Stephan J. L. A1 - Bansal, Nisha A1 - Baptista, Daniela A1 - Bergmann, Sven A1 - Biggs, Mary L. A1 - Biino, Ginevra A1 - Boehnke, Michael A1 - Boerwinkle, Eric A1 - Boissel, Mathilde A1 - Böttinger, Erwin A1 - Boutin, Thibaud S. A1 - Brenner, Hermann A1 - Brumat, Marco A1 - Burkhardt, Ralph A1 - Butterworth, Adam S. A1 - Campana, Eric A1 - Campbell, Archie A1 - Campbell, Harry A1 - Canouil, Mickael A1 - Carroll, Robert J. A1 - Catamo, Eulalia A1 - Chambers, John C. A1 - Chee, Miao-Ling A1 - Chee, Miao-Li A1 - Chen, Xu A1 - Cheng, Ching-Yu A1 - Cheng, Yurong A1 - Christensen, Kaare A1 - Cifkova, Renata A1 - Ciullo, Marina A1 - Concas, Maria Pina A1 - Cook, James P. A1 - Coresh, Josef A1 - Corre, Tanguy A1 - Sala, Cinzia Felicita A1 - Cusi, Daniele A1 - Danesh, John A1 - Daw, E. Warwick A1 - De Borst, Martin H. A1 - De Grandi, Alessandro A1 - De Mutsert, Renee A1 - De Vries, Aiko P. J. A1 - Degenhardt, Frauke A1 - Delgado, Graciela A1 - Demirkan, Ayse A1 - Di Angelantonio, Emanuele A1 - Dittrich, Katalin A1 - Divers, Jasmin A1 - Dorajoo, Rajkumar A1 - Eckardt, Kai-Uwe A1 - Ehret, Georg A1 - Elliott, Paul A1 - Endlich, Karlhans A1 - Evans, Michele K. A1 - Felix, Janine F. A1 - Foo, Valencia Hui Xian A1 - Franco, Oscar H. A1 - Franke, Andre A1 - Freedman, Barry I. A1 - Freitag-Wolf, Sandra A1 - Friedlander, Yechiel A1 - Froguel, Philippe A1 - Gansevoort, Ron T. A1 - Gao, He A1 - Gasparini, Paolo A1 - Gaziano, J. Michael A1 - Giedraitis, Vilmantas A1 - Gieger, Christian A1 - Girotto, Giorgia A1 - Giulianini, Franco A1 - Gogele, Martin A1 - Gordon, Scott D. A1 - Gudbjartsson, Daniel F. A1 - Gudnason, Vilmundur A1 - Haller, Toomas A1 - Hamet, Pavel A1 - Harris, Tamara B. A1 - Hartman, Catharina A. A1 - Hayward, Caroline A1 - Hellwege, Jacklyn N. A1 - Heng, Chew-Kiat A1 - Hicks, Andrew A. A1 - Hofer, Edith A1 - Huang, Wei A1 - Hutri-Kahonen, Nina A1 - Hwang, Shih-Jen A1 - Ikram, M. Arfan A1 - Indridason, Olafur S. A1 - Ingelsson, Erik A1 - Ising, Marcus A1 - Jaddoe, Vincent W. V. A1 - Jakobsdottir, Johanna A1 - Jonas, Jost B. A1 - Joshi, Peter K. A1 - Josyula, Navya Shilpa A1 - Jung, Bettina A1 - Kahonen, Mika A1 - Kamatani, Yoichiro A1 - Kammerer, Candace M. A1 - Kanai, Masahiro A1 - Kastarinen, Mika A1 - Kerr, Shona M. A1 - Khor, Chiea-Chuen A1 - Kiess, Wieland A1 - Kleber, Marcus E. A1 - Koenig, Wolfgang A1 - Kooner, Jaspal S. A1 - Korner, Antje A1 - Kovacs, Peter A1 - Kraja, Aldi T. A1 - Krajcoviechova, Alena A1 - Kramer, Holly A1 - Kramer, Bernhard K. A1 - Kronenberg, Florian A1 - Kubo, Michiaki A1 - Kuhnel, Brigitte A1 - Kuokkanen, Mikko A1 - Kuusisto, Johanna A1 - La Bianca, Martina A1 - Laakso, Markku A1 - Lange, Leslie A. A1 - Langefeld, Carl D. A1 - Lee, Jeannette Jen-Mai A1 - Lehne, Benjamin A1 - Lehtimaki, Terho A1 - Lieb, Wolfgang A1 - Lim, Su-Chi A1 - Lind, Lars A1 - Lindgren, Cecilia M. A1 - Liu, Jun A1 - Liu, Jianjun A1 - Loeffler, Markus A1 - Loos, Ruth J. F. A1 - Lucae, Susanne A1 - Lukas, Mary Ann A1 - Lyytikainen, Leo-Pekka A1 - Magi, Reedik A1 - Magnusson, Patrik K. E. A1 - Mahajan, Anubha A1 - Martin, Nicholas G. A1 - Martins, Jade A1 - Marz, Winfried A1 - Mascalzoni, Deborah A1 - Matsuda, Koichi A1 - Meisinger, Christa A1 - Meitinger, Thomas A1 - Melander, Olle A1 - Metspalu, Andres A1 - Mikaelsdottir, Evgenia K. A1 - Milaneschi, Yuri A1 - Miliku, Kozeta A1 - Mishra, Pashupati P. A1 - Program, V. A. Million Veteran A1 - Mohlke, Karen L. A1 - Mononen, Nina A1 - Montgomery, Grant W. A1 - Mook-Kanamori, Dennis O. A1 - Mychaleckyj, Josyf C. A1 - Nadkarni, Girish N. A1 - Nalls, Mike A. A1 - Nauck, Matthias A1 - Nikus, Kjell A1 - Ning, Boting A1 - Nolte, Ilja M. A1 - Noordam, Raymond A1 - Olafsson, Isleifur A1 - Oldehinkel, Albertine J. A1 - Orho-Melander, Marju A1 - Ouwehand, Willem H. A1 - Padmanabhan, Sandosh A1 - Palmer, Nicholette D. A1 - Palsson, Runolfur A1 - Penninx, Brenda W. J. H. A1 - Perls, Thomas A1 - Perola, Markus A1 - Pirastu, Mario A1 - Pirastu, Nicola A1 - Pistis, Giorgio A1 - Podgornaia, Anna I. A1 - Polasek, Ozren A1 - Ponte, Belen A1 - Porteous, David J. A1 - Poulain, Tanja A1 - Pramstaller, Peter P. A1 - Preuss, Michael H. A1 - Prins, Bram P. A1 - Province, Michael A. A1 - Rabelink, Ton J. A1 - Raffield, Laura M. A1 - Raitakari, Olli T. A1 - Reilly, Dermot F. A1 - Rettig, Rainer A1 - Rheinberger, Myriam A1 - Rice, Kenneth M. A1 - Ridker, Paul M. A1 - Rivadeneira, Fernando A1 - Rizzi, Federica A1 - Roberts, David J. A1 - Robino, Antonietta A1 - Rossing, Peter A1 - Rudan, Igor A1 - Rueedi, Rico A1 - Ruggiero, Daniela A1 - Ryan, Kathleen A. A1 - Saba, Yasaman A1 - Sabanayagam, Charumathi A1 - Salomaa, Veikko A1 - Salvi, Erika A1 - Saum, Kai-Uwe A1 - Schmidt, Helena A1 - Schmidt, Reinhold A1 - Ben Schottker, A1 - Schulz, Christina-Alexandra A1 - Schupf, Nicole A1 - Shaffer, Christian M. A1 - Shi, Yuan A1 - Smith, Albert V. A1 - Smith, Blair H. A1 - Soranzo, Nicole A1 - Spracklen, Cassandra N. A1 - Strauch, Konstantin A1 - Stringham, Heather M. A1 - Stumvoll, Michael A1 - Svensson, Per O. A1 - Szymczak, Silke A1 - Tai, E-Shyong A1 - Tajuddin, Salman M. A1 - Tan, Nicholas Y. Q. A1 - Taylor, Kent D. A1 - Teren, Andrej A1 - Tham, Yih-Chung A1 - Thiery, Joachim A1 - Thio, Chris H. L. A1 - Thomsen, Hauke A1 - Thorleifsson, Gudmar A1 - Toniolo, Daniela A1 - Tonjes, Anke A1 - Tremblay, Johanne A1 - Tzoulaki, Ioanna A1 - Uitterlinden, Andre G. A1 - Vaccargiu, Simona A1 - Van Dam, Rob M. A1 - Van der Harst, Pim A1 - Van Duijn, Cornelia M. A1 - Edward, Digna R. Velez A1 - Verweij, Niek A1 - Vogelezang, Suzanne A1 - Volker, Uwe A1 - Vollenweider, Peter A1 - Waeber, Gerard A1 - Waldenberger, Melanie A1 - Wallentin, Lars A1 - Wang, Ya Xing A1 - Wang, Chaolong A1 - Waterworth, Dawn M. A1 - Bin Wei, Wen A1 - White, Harvey A1 - Whitfield, John B. A1 - Wild, Sarah H. A1 - Wilson, James F. A1 - Wojczynski, Mary K. A1 - Wong, Charlene A1 - Wong, Tien-Yin A1 - Xu, Liang A1 - Yang, Qiong A1 - Yasuda, Masayuki A1 - Yerges-Armstrong, Laura M. A1 - Zhang, Weihua A1 - Zonderman, Alan B. A1 - Rotter, Jerome I. A1 - Bochud, Murielle A1 - Psaty, Bruce M. A1 - Vitart, Veronique A1 - Wilson, James G. A1 - Dehghan, Abbas A1 - Parsa, Afshin A1 - Chasman, Daniel I. A1 - Ho, Kevin A1 - Morris, Andrew P. A1 - Devuyst, Olivier A1 - Akilesh, Shreeram A1 - Pendergrass, Sarah A. A1 - Sim, Xueling A1 - Boger, Carsten A. A1 - Okada, Yukinori A1 - Edwards, Todd L. A1 - Snieder, Harold A1 - Stefansson, Kari A1 - Hung, Adriana M. A1 - Heid, Iris M. A1 - Scholz, Markus A1 - Teumer, Alexander A1 - Kottgen, Anna A1 - Pattaro, Cristian T1 - A catalog of genetic loci associated with kidney function from analyses of a million individuals JF - Nature genetics N2 - Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research. Y1 - 2019 U6 - https://doi.org/10.1038/s41588-019-0407-x SN - 1061-4036 SN - 1546-1718 VL - 51 IS - 6 SP - 957 EP - + PB - Nature Publ. Group CY - New York ER - TY - BOOK A1 - Adriano, Christian A1 - Bleifuß, Tobias A1 - Cheng, Lung-Pan A1 - Diba, Kiarash A1 - Fricke, Andreas A1 - Grapentin, Andreas A1 - Jiang, Lan A1 - Kovacs, Robert A1 - Krejca, Martin Stefan A1 - Mandal, Sankalita A1 - Marwecki, Sebastian A1 - Matthies, Christoph A1 - Mattis, Toni A1 - Niephaus, Fabio A1 - Pirl, Lukas A1 - Quinzan, Francesco A1 - Ramson, Stefan A1 - Rezaei, Mina A1 - Risch, Julian A1 - Rothenberger, Ralf A1 - Roumen, Thijs A1 - Stojanovic, Vladeta A1 - Wolf, Johannes ED - Meinel, Christoph ED - Plattner, Hasso ED - Döllner, Jürgen Roland Friedrich ED - Weske, Mathias ED - Polze, Andreas ED - Hirschfeld, Robert ED - Naumann, Felix ED - Giese, Holger ED - Baudisch, Patrick ED - Friedrich, Tobias ED - Böttinger, Erwin ED - Lippert, Christoph T1 - Technical report BT - Fall Retreat 2018 N2 - Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application. Commonly used technologies, such as J2EE and .NET, form de facto standards for the realization of complex distributed systems. Evolution of component systems has lead to web services and service-based architectures. This has been manifested in a multitude of industry standards and initiatives such as XML, WSDL UDDI, SOAP, etc. All these achievements lead to a new and promising paradigm in IT systems engineering which proposes to design complex software solutions as collaboration of contractually defined software services. Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns. The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment. N2 - Der Entwurf und die Realisierung dienstbasierender Architekturen wirft eine Vielzahl von Forschungsfragestellungen aus den Gebieten der Softwaretechnik, der Systemmodellierung und -analyse, sowie der Adaptierbarkeit und Integration von Applikationen auf. Komponentenorientierung und WebServices sind zwei Ansätze für den effizienten Entwurf und die Realisierung komplexer Web-basierender Systeme. Sie ermöglichen die Reaktion auf wechselnde Anforderungen ebenso, wie die Integration großer komplexer Softwaresysteme. Heute übliche Technologien, wie J2EE und .NET, sind de facto Standards für die Entwicklung großer verteilter Systeme. Die Evolution solcher Komponentensysteme führt über WebServices zu dienstbasierenden Architekturen. Dies manifestiert sich in einer Vielzahl von Industriestandards und Initiativen wie XML, WSDL, UDDI, SOAP. All diese Schritte führen letztlich zu einem neuen, vielversprechenden Paradigma für IT Systeme, nach dem komplexe Softwarelösungen durch die Integration vertraglich vereinbarter Software-Dienste aufgebaut werden sollen. "Service-Oriented Systems Engineering" repräsentiert die Symbiose bewährter Praktiken aus den Gebieten der Objektorientierung, der Komponentenprogrammierung, des verteilten Rechnen sowie der Geschäftsprozesse und berücksichtigt auch die Integration von Geschäftsanliegen und Informationstechnologien. Die Klausurtagung des Forschungskollegs "Service-oriented Systems Engineering" findet einmal jährlich statt und bietet allen Kollegiaten die Möglichkeit den Stand ihrer aktuellen Forschung darzulegen. Bedingt durch die Querschnittstruktur des Kollegs deckt dieser Bericht ein weites Spektrum aktueller Forschungsthemen ab. Dazu zählen unter anderem Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; sowie Services Specification, Composition, and Enactment. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 129 KW - Hasso Plattner Institute KW - research school KW - Ph.D. retreat KW - service-oriented systems engineering KW - Hasso-Plattner-Institut KW - Forschungskolleg KW - Klausurtagung KW - Service-oriented Systems Engineering Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427535 SN - 978-3-86956-465-4 SN - 1613-5652 SN - 2191-1665 IS - 129 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Gorski, Mathias A1 - Jung, Bettina A1 - Li, Yong A1 - Matias-Garcia, Pamela R. A1 - Wuttke, Matthias A1 - Coassin, Stefan A1 - Thio, Chris H. L. A1 - Kleber, Marcus E. A1 - Winkler, Thomas W. A1 - Wanner, Veronika A1 - Chai, Jin-Fang A1 - Chu, Audrey Y. A1 - Cocca, Massimiliano A1 - Feitosa, Mary F. A1 - Ghasemi, Sahar A1 - Hoppmann, Anselm A1 - Horn, Katrin A1 - Li, Man A1 - Nutile, Teresa A1 - Scholz, Markus A1 - Sieber, Karsten B. A1 - Teumer, Alexander A1 - Tin, Adrienne A1 - Wang, Judy A1 - Tayo, Bamidele O. A1 - Ahluwalia, Tarunveer S. A1 - Almgren, Peter A1 - Bakker, Stephan J. L. A1 - Banas, Bernhard A1 - Bansal, Nisha A1 - Biggs, Mary L. A1 - Boerwinkle, Eric A1 - Böttinger, Erwin A1 - Brenner, Hermann A1 - Carroll, Robert J. A1 - Chalmers, John A1 - Chee, Miao-Li A1 - Chee, Miao-Ling A1 - Cheng, Ching-Yu A1 - Coresh, Josef A1 - de Borst, Martin H. A1 - Degenhardt, Frauke A1 - Eckardt, Kai-Uwe A1 - Endlich, Karlhans A1 - Franke, Andre A1 - Freitag-Wolf, Sandra A1 - Gampawar, Piyush A1 - Gansevoort, Ron T. A1 - Ghanbari, Mohsen A1 - Gieger, Christian A1 - Hamet, Pavel A1 - Ho, Kevin A1 - Hofer, Edith A1 - Holleczek, Bernd A1 - Foo, Valencia Hui Xian A1 - Hutri-Kahonen, Nina A1 - Hwang, Shih-Jen A1 - Ikram, M. Arfan A1 - Josyula, Navya Shilpa A1 - Kahonen, Mika A1 - Khor, Chiea-Chuen A1 - Koenig, Wolfgang A1 - Kramer, Holly A1 - Kraemer, Bernhard K. A1 - Kuehnel, Brigitte A1 - Lange, Leslie A. A1 - Lehtimaki, Terho A1 - Lieb, Wolfgang A1 - Loos, Ruth J. F. A1 - Lukas, Mary Ann A1 - Lyytikainen, Leo-Pekka A1 - Meisinger, Christa A1 - Meitinger, Thomas A1 - Melander, Olle A1 - Milaneschi, Yuri A1 - Mishra, Pashupati P. A1 - Mononen, Nina A1 - Mychaleckyj, Josyf C. A1 - Nadkarni, Girish N. A1 - Nauck, Matthias A1 - Nikus, Kjell A1 - Ning, Boting A1 - Nolte, Ilja M. A1 - O'Donoghue, Michelle L. A1 - Orho-Melander, Marju A1 - Pendergrass, Sarah A. A1 - Penninx, Brenda W. J. H. A1 - Preuss, Michael H. A1 - Psaty, Bruce M. A1 - Raffield, Laura M. A1 - Raitakari, Olli T. A1 - Rettig, Rainer A1 - Rheinberger, Myriam A1 - Rice, Kenneth M. A1 - Rosenkranz, Alexander R. A1 - Rossing, Peter A1 - Rotter, Jerome A1 - Sabanayagam, Charumathi A1 - Schmidt, Helena A1 - Schmidt, Reinhold A1 - Schoettker, Ben A1 - Schulz, Christina-Alexandra A1 - Sedaghat, Sanaz A1 - Shaffer, Christian M. A1 - Strauch, Konstantin A1 - Szymczak, Silke A1 - Taylor, Kent D. A1 - Tremblay, Johanne A1 - Chaker, Layal A1 - van der Harst, Pim A1 - van der Most, Peter J. A1 - Verweij, Niek A1 - Voelker, Uwe A1 - Waldenberger, Melanie A1 - Wallentin, Lars A1 - Waterworth, Dawn M. A1 - White, Harvey D. A1 - Wilson, James G. A1 - Wong, Tien-Yin A1 - Woodward, Mark A1 - Yang, Qiong A1 - Yasuda, Masayuki A1 - Yerges-Armstrong, Laura M. A1 - Zhang, Yan A1 - Snieder, Harold A1 - Wanner, Christoph A1 - Boger, Carsten A. A1 - Kottgen, Anna A1 - Kronenberg, Florian A1 - Pattaro, Cristian A1 - Heid, Iris M. T1 - Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline JF - Kidney international : official journal of the International Society of Nephrology N2 - Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m(2)/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m(2) at follow-up among those with eGFRcrea 60 mL/min/1.73m(2) or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or (LARP4B). Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function. KW - acute kidney injury KW - end-stage kidney disease KW - genome-wide association KW - study KW - rapid eGFRcrea decline Y1 - 2020 U6 - https://doi.org/10.1016/j.kint.2020.09.030 SN - 0085-2538 SN - 1523-1755 VL - 99 IS - 4 SP - 926 EP - 939 PB - Elsevier CY - New York ER - TY - THES A1 - Taleb, Aiham T1 - Self-supervised deep learning methods for medical image analysis T1 - Selbstüberwachte Deep Learning Methoden für die medizinische Bildanalyse N2 - Deep learning has seen widespread application in many domains, mainly for its ability to learn data representations from raw input data. Nevertheless, its success has so far been coupled with the availability of large annotated (labelled) datasets. This is a requirement that is difficult to fulfil in several domains, such as in medical imaging. Annotation costs form a barrier in extending deep learning to clinically-relevant use cases. The labels associated with medical images are scarce, since the generation of expert annotations of multimodal patient data at scale is non-trivial, expensive, and time-consuming. This substantiates the need for algorithms that learn from the increasing amounts of unlabeled data. Self-supervised representation learning algorithms offer a pertinent solution, as they allow solving real-world (downstream) deep learning tasks with fewer annotations. Self-supervised approaches leverage unlabeled samples to acquire generic features about different concepts, enabling annotation-efficient downstream task solving subsequently. Nevertheless, medical images present multiple unique and inherent challenges for existing self-supervised learning approaches, which we seek to address in this thesis: (i) medical images are multimodal, and their multiple modalities are heterogeneous in nature and imbalanced in quantities, e.g. MRI and CT; (ii) medical scans are multi-dimensional, often in 3D instead of 2D; (iii) disease patterns in medical scans are numerous and their incidence exhibits a long-tail distribution, so it is oftentimes essential to fuse knowledge from different data modalities, e.g. genomics or clinical data, to capture disease traits more comprehensively; (iv) Medical scans usually exhibit more uniform color density distributions, e.g. in dental X-Rays, than natural images. Our proposed self-supervised methods meet these challenges, besides significantly reducing the amounts of required annotations. We evaluate our self-supervised methods on a wide array of medical imaging applications and tasks. Our experimental results demonstrate the obtained gains in both annotation-efficiency and performance; our proposed methods outperform many approaches from related literature. Additionally, in case of fusion with genetic modalities, our methods also allow for cross-modal interpretability. In this thesis, not only we show that self-supervised learning is capable of mitigating manual annotation costs, but also our proposed solutions demonstrate how to better utilize it in the medical imaging domain. Progress in self-supervised learning has the potential to extend deep learning algorithms application to clinical scenarios. N2 - Deep Learning findet in vielen Bereichen breite Anwendung, vor allem wegen seiner Fähigkeit, Datenrepräsentationen aus rohen Eingabedaten zu lernen. Dennoch war der Erfolg bisher an die Verfügbarkeit großer annotatierter Datensätze geknüpft. Dies ist eine Anforderung, die in verschiedenen Bereichen, z. B. in der medizinischen Bildgebung, schwer zu erfüllen ist. Die Kosten für die Annotation stellen ein Hindernis für die Ausweitung des Deep Learning auf klinisch relevante Anwendungsfälle dar. Die mit medizinischen Bildern verbundenen Annotationen sind rar, da die Erstellung von Experten Annotationen für multimodale Patientendaten in großem Umfang nicht trivial, teuer und zeitaufwändig ist. Dies unterstreicht den Bedarf an Algorithmen, die aus den wachsenden Mengen an unbeschrifteten Daten lernen. Selbstüberwachte Algorithmen für das Repräsentationslernen bieten eine mögliche Lösung, da sie die Lösung realer (nachgelagerter) Deep-Learning-Aufgaben mit weniger Annotationen ermöglichen. Selbstüberwachte Ansätze nutzen unannotierte Stichproben, um generisches Eigenschaften über verschiedene Konzepte zu erlangen und ermöglichen so eine annotationseffiziente Lösung nachgelagerter Aufgaben. Medizinische Bilder stellen mehrere einzigartige und inhärente Herausforderungen für existierende selbstüberwachte Lernansätze dar, die wir in dieser Arbeit angehen wollen: (i) medizinische Bilder sind multimodal, und ihre verschiedenen Modalitäten sind von Natur aus heterogen und in ihren Mengen unausgewogen, z.B. (ii) medizinische Scans sind mehrdimensional, oft in 3D statt in 2D; (iii) Krankheitsmuster in medizinischen Scans sind zahlreich und ihre Häufigkeit weist eine Long-Tail-Verteilung auf, so dass es oft unerlässlich ist, Wissen aus verschiedenen Datenmodalitäten, z. B. Genomik oder klinische Daten, zu verschmelzen, um Krankheitsmerkmale umfassender zu erfassen; (iv) medizinische Scans weisen in der Regel eine gleichmäßigere Farbdichteverteilung auf, z. B. in zahnmedizinischen Röntgenaufnahmen, als natürliche Bilder. Die von uns vorgeschlagenen selbstüberwachten Methoden adressieren diese Herausforderungen und reduzieren zudem die Menge der erforderlichen Annotationen erheblich. Wir evaluieren unsere selbstüberwachten Methoden in verschiedenen Anwendungen und Aufgaben der medizinischen Bildgebung. Unsere experimentellen Ergebnisse zeigen, dass die von uns vorgeschlagenen Methoden sowohl die Effizienz der Annotation als auch die Leistung steigern und viele Ansätze aus der verwandten Literatur übertreffen. Darüber hinaus ermöglichen unsere Methoden im Falle der Fusion mit genetischen Modalitäten auch eine modalübergreifende Interpretierbarkeit. In dieser Arbeit zeigen wir nicht nur, dass selbstüberwachtes Lernen in der Lage ist, die Kosten für manuelle Annotationen zu senken, sondern auch, wie man es in der medizinischen Bildgebung besser nutzen kann. Fortschritte beim selbstüberwachten Lernen haben das Potenzial, die Anwendung von Deep-Learning-Algorithmen auf klinische Szenarien auszuweiten. KW - Artificial Intelligence KW - machine learning KW - unsupervised learning KW - representation learning KW - Künstliche Intelligenz KW - maschinelles Lernen KW - Representationlernen KW - selbstüberwachtes Lernen Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-644089 ER - TY - JOUR A1 - Shams, Boshra A1 - Wang, Ziqian A1 - Roine, Timo A1 - Aydogan, Dogu Baran A1 - Vajkoczy, Peter A1 - Lippert, Christoph A1 - Picht, Thomas A1 - Fekonja, Lucius Samo T1 - Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract JF - Brain communications N2 - Shams et al. report that glioma patients' motor status is predicted accurately by diffusion MRI metrics along the corticospinal tract based on support vector machine method, reaching an overall accuracy of 77%. They show that these metrics are more effective than demographic and clinical variables. Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 +/- 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts' profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model's performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits. KW - machine learning KW - support vector machine KW - tractography KW - diffusion MRI; KW - corticospinal tract Y1 - 2022 U6 - https://doi.org/10.1093/braincomms/fcac141 SN - 2632-1297 VL - 4 IS - 3 PB - Oxford University Press CY - Oxford ER - TY - JOUR A1 - Ehrig, Lukas A1 - Wagner, Ann-Christin A1 - Wolter, Heike A1 - Correll, Christoph U. A1 - Geisel, Olga A1 - Konigorski, Stefan T1 - FASDetect as a machine learning-based screening app for FASD in youth with ADHD JF - npj Digital Medicine N2 - Fetal alcohol-spectrum disorder (FASD) is underdiagnosed and often misdiagnosed as attention-deficit/hyperactivity disorder (ADHD). Here, we develop a screening tool for FASD in youth with ADHD symptoms. To develop the prediction model, medical record data from a German University outpatient unit are assessed including 275 patients aged 0-19 years old with FASD with or without ADHD and 170 patients with ADHD without FASD aged 0-19 years old. We train 6 machine learning models based on 13 selected variables and evaluate their performance. Random forest models yield the best prediction models with a cross-validated AUC of 0.92 (95% confidence interval [0.84, 0.99]). Follow-up analyses indicate that a random forest model with 6 variables - body length and head circumference at birth, IQ, socially intrusive behaviour, poor memory and sleep disturbance - yields equivalent predictive accuracy. We implement the prediction model in a web-based app called FASDetect - a user-friendly, clinically scalable FASD risk calculator that is freely available at https://fasdetect.dhc-lab.hpi.de. KW - Medical research KW - Psychiatric disorders Y1 - 2023 U6 - https://doi.org/10.1038/s41746-023-00864-1 SN - 2398-6352 VL - 6 IS - 1 PB - Macmillan Publishers Limited CY - Basingstoke ER - TY - JOUR A1 - Slosarek, Tamara A1 - Ibing, Susanne A1 - Schormair, Barbara A1 - Heyne, Henrike A1 - Böttinger, Erwin A1 - Andlauer, Till A1 - Schurmann, Claudia T1 - Implementation and evaluation of personal genetic testing as part of genomics analysis courses in German universities JF - BMC Medical Genomics N2 - Purpose Due to the increasing application of genome analysis and interpretation in medical disciplines, professionals require adequate education. Here, we present the implementation of personal genotyping as an educational tool in two genomics courses targeting Digital Health students at the Hasso Plattner Institute (HPI) and medical students at the Technical University of Munich (TUM). Methods We compared and evaluated the courses and the students ' perceptions on the course setup using questionnaires. Results During the course, students changed their attitudes towards genotyping (HPI: 79% [15 of 19], TUM: 47% [25 of 53]). Predominantly, students became more critical of personal genotyping (HPI: 73% [11 of 15], TUM: 72% [18 of 25]) and most students stated that genetic analyses should not be allowed without genetic counseling (HPI: 79% [15 of 19], TUM: 70% [37 of 53]). Students found the personal genotyping component useful (HPI: 89% [17 of 19], TUM: 92% [49 of 53]) and recommended its inclusion in future courses (HPI: 95% [18 of 19], TUM: 98% [52 of 53]). Conclusion Students perceived the personal genotyping component as valuable in the described genomics courses. The implementation described here can serve as an example for future courses in Europe. KW - Genomics education KW - Personal genotyping KW - Personalized medicine Y1 - 2023 U6 - https://doi.org/10.1186/s12920-023-01503-0 SN - 1755-8794 VL - 16 IS - 1 PB - BMC CY - London ER - TY - JOUR A1 - Ulrich, Jens-Uwe A1 - Lutfi, Ahmad A1 - Rutzen, Kilian A1 - Renard, Bernhard Y. T1 - ReadBouncer BT - precise and scalable adaptive sampling for nanopore sequencing JF - Bioinformatics N2 - Motivation: Nanopore sequencers allow targeted sequencing of interesting nucleotide sequences by rejecting other sequences from individual pores. This feature facilitates the enrichment of low-abundant sequences by depleting overrepresented ones in-silico. Existing tools for adaptive sampling either apply signal alignment, which cannot handle human-sized reference sequences, or apply read mapping in sequence space relying on fast graphical processing units (GPU) base callers for real-time read rejection. Using nanopore long-read mapping tools is also not optimal when mapping shorter reads as usually analyzed in adaptive sampling applications. Results: Here, we present a new approach for nanopore adaptive sampling that combines fast CPU and GPU base calling with read classification based on Interleaved Bloom Filters. ReadBouncer improves the potential enrichment of low abundance sequences by its high read classification sensitivity and specificity, outperforming existing tools in the field. It robustly removes even reads belonging to large reference sequences while running on commodity hardware without GPUs, making adaptive sampling accessible for in-field researchers. Readbouncer also provides a user-friendly interface and installer files for end-users without a bioinformatics background. Y1 - 2022 U6 - https://doi.org/10.1093/bioinformatics/btac223 SN - 1367-4803 SN - 1367-4811 VL - 38 IS - SUPPL 1 SP - 153 EP - 160 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Vitagliano, Gerardo A1 - Hameed, Mazhar A1 - Jiang, Lan A1 - Reisener, Lucas A1 - Wu, Eugene A1 - Naumann, Felix T1 - Pollock: a data loading benchmark JF - Proceedings of the VLDB Endowment N2 - Any system at play in a data-driven project has a fundamental requirement: the ability to load data. The de-facto standard format to distribute and consume raw data is CSV. Yet, the plain text and flexible nature of this format make such files often difficult to parse and correctly load their content, requiring cumbersome data preparation steps. We propose a benchmark to assess the robustness of systems in loading data from non-standard CSV formats and with structural inconsistencies. First, we formalize a model to describe the issues that affect real-world files and use it to derive a systematic lpollutionz process to generate dialects for any given grammar. Our benchmark leverages the pollution framework for the csv format. To guide pollution, we have surveyed thousands of real-world, publicly available csv files, recording the problems we encountered. We demonstrate the applicability of our benchmark by testing and scoring 16 different systems: popular csv parsing frameworks, relational database tools, spreadsheet systems, and a data visualization tool. Y1 - 2023 U6 - https://doi.org/10.14778/3594512.3594518 SN - 2150-8097 VL - 16 IS - 8 SP - 1870 EP - 1882 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Dressler, Falko A1 - Chiasserini, Carla Fabiana A1 - Fitzek, Frank H. P. A1 - Karl, Holger A1 - Cigno, Renato Lo A1 - Capone, Antonio A1 - Casetti, Claudio A1 - Malandrino, Francesco A1 - Mancuso, Vincenzo A1 - Klingler, Florian A1 - Rizzo, Gianluca T1 - V-Edge BT - virtual edge computing as an enabler for novel microservices and cooperative computing JF - IEEE network N2 - As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: Instead of sending all data and tasks from an end user's device to the cloud, possibly covering thousands of kilometers and introducing delays lower-bounded by propagation speed, edge servers deployed in close proximity to the user (e.g., at some base station) serve as proxy for the cloud. This is particularly interesting for upcoming machine-learning-based intelligent services, which require substantial computational and networking performance for continuous model training. However, this promising idea is hampered by the limited number of such edge servers. In this article, we discuss a way forward, namely the V-Edge concept. V-Edge helps bridge the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available. Thus, V-Edge acts as an enabler for novel microservices as well as cooperative computing solutions in next-generation networks. We introduce the general V-Edge architecture, and we characterize some of the key research challenges to overcome in order to enable wide-spread and intelligent edge services. KW - Training KW - Performance evaluation KW - Cloud computing KW - Microservice KW - architectures KW - Computer architecture KW - Delays KW - Servers Y1 - 2022 U6 - https://doi.org/10.1109/MNET.001.2100491 SN - 0890-8044 SN - 1558-156X VL - 36 IS - 3 SP - 24 EP - 31 PB - Inst. of Electr. and Electronics Engineers CY - Piscataway ER - TY - JOUR A1 - Kühne, Katharina A1 - Herbold, Erika A1 - Bendel, Oliver A1 - Zhou, Yuefang A1 - Fischer, Martin H. T1 - “Ick bin een Berlina” BT - dialect proficiency impacts a robot’s trustworthiness and competence evaluation JF - Frontiers in robotics and AI N2 - Background: Robots are increasingly used as interaction partners with humans. Social robots are designed to follow expected behavioral norms when engaging with humans and are available with different voices and even accents. Some studies suggest that people prefer robots to speak in the user’s dialect, while others indicate a preference for different dialects. Methods: Our study examined the impact of the Berlin dialect on perceived trustworthiness and competence of a robot. One hundred and twenty German native speakers (Mage = 32 years, SD = 12 years) watched an online video featuring a NAO robot speaking either in the Berlin dialect or standard German and assessed its trustworthiness and competence. Results: We found a positive relationship between participants’ self-reported Berlin dialect proficiency and trustworthiness in the dialect-speaking robot. Only when controlled for demographic factors, there was a positive association between participants’ dialect proficiency, dialect performance and their assessment of robot’s competence for the standard German-speaking robot. Participants’ age, gender, length of residency in Berlin, and device used to respond also influenced assessments. Finally, the robot’s competence positively predicted its trustworthiness. Discussion: Our results inform the design of social robots and emphasize the importance of device control in online experiments. KW - competence KW - dialect KW - human-robot interaction KW - robot voice KW - social robot KW - trust Y1 - 2024 U6 - https://doi.org/10.3389/frobt.2023.1241519 SN - 2296-9144 VL - 10 PB - Frontiers Media S.A. CY - Lausanne ER -