@article{AdnanSrsicVenticichetal.2020,
  author    = {Adnan, Hassan Sami and Srsic, Amanda and Venticich, Pete Milos and Townend, David M.R.},
  title     = {Using AI for mental health analysis and prediction in school surveys},
  series = {European journal of public health},
  volume    = {30},
  journal   = {European journal of public health},
  publisher = {Oxford Univ. Press},
  address   = {Oxford [u.a.]},
  issn      = {1101-1262},
  doi       = {10.1093/eurpub/ckaa165.336},
  pages     = {V125 -- V125},
  year      = {2020},
  abstract  = {Background: Childhood and adolescence are critical stages of life for mental health and well-being. Schools are a key setting for mental health promotion and illness prevention. One in five children and adolescents have a mental disorder, about half of mental disorders beginning before the age of 14. Beneficial and explainable artificial intelligence can replace current paper- based and online approaches to school mental health surveys. This can enhance data acquisition, interoperability, data driven analysis, trust and compliance. This paper presents a model for using chatbots for non-obtrusive data collection and supervised machine learning models for data analysis; and discusses ethical considerations pertaining to the use of these models. Methods: For data acquisition, the proposed model uses chatbots which interact with students. The conversation log acts as the source of raw data for the machine learning. Pre-processing of the data is automated by filtering for keywords and phrases. Existing survey results, obtained through current paper-based data collection methods, are evaluated by domain experts (health professionals). These can be used to create a test dataset to validate the machine learning models. Supervised learning can then be deployed to classify specific behaviour and mental health patterns. Results: We present a model that can be used to improve upon current paper-based data collection and manual data analysis methods. An open-source GitHub repository contains necessary tools and components of this model. Privacy is respected through rigorous observance of confidentiality and data protection requirements. Critical reflection on these ethics and law aspects is included in the project. Conclusions: This model strengthens mental health surveillance in schools. The same tools and components could be applied to other public health data. Future extensions of this model could also incorporate unsupervised learning to find clusters and patterns of unknown effects.},
  language  = {en}
}
@book{OPUS4-6813,
  title     = {Cloud security mechanisms},
  number    = {87},
  editor    = {Neuhaus, Christian and Polze, Andreas},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-281-0},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-68168},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {78},
  year      = {2014},
  abstract  = {Cloud computing has brought great benefits in cost and flexibility for provisioning services. The greatest challenge of cloud computing remains however the question of security. The current standard tools in access control mechanisms and cryptography can only partly solve the security challenges of cloud infrastructures. In the recent years of research in security and cryptography, novel mechanisms, protocols and algorithms have emerged that offer new ways to create secure services atop cloud infrastructures. This report provides introductions to a selection of security mechanisms that were part of the "Cloud Security Mechanisms" seminar in summer term 2013 at HPI.},
  language  = {en}
}
@book{NeuhausPolzeChowdhuryy2011,
  author    = {Neuhaus, Christian and Polze, Andreas and Chowdhuryy, Mohammad M. R.},
  title     = {Survey on healthcare IT systems : standards, regulations and security},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-128-8},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-51463},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {53},
  year      = {2011},
  abstract  = {IT systems for healthcare are a complex and exciting field. One the one hand, there is a vast number of improvements and work alleviations that computers can bring to everyday healthcare. Some ways of treatment, diagnoses and organisational tasks were even made possible by computer usage in the first place. On the other hand, there are many factors that encumber computer usage and make development of IT systems for healthcare a challenging, sometimes even frustrating task. These factors are not solely technology-related, but just as well social or economical conditions. This report describes some of the idiosyncrasies of IT systems in the healthcare domain, with a special focus on legal regulations, standards and security.},
  language  = {en}
}