@article{AdnanMatthewsHackletal.2020,
  author    = {Adnan, Hassan Sami and Matthews, Sam and Hackl, M. and Das, P. P. and Manaswini, Manisha and Gadamsetti, S. and Filali, Maroua and Owoyele, Babajide and Santuber, Joaqu{\´i}n and Edelman, Jonathan},
  title     = {Human centered AI design for clinical monitoring and data management},
  series = {European journal of public health : official journal of the European Health Association},
  volume    = {30},
  journal   = {European journal of public health : official journal of the European Health Association},
  number    = {5},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {1101-1262},
  doi       = {10.1093/eurpub/ckaa165.225},
  pages     = {V86 -- V86},
  year      = {2020},
  abstract  = {In clinical settings, significant resources are spent on data collection and monitoring patients' health parameters to improve decision-making and provide better care. With increased digitization, the healthcare sector is shifting towards implementing digital technologies for data management and in administration. New technologies offer better treatment opportunities and streamline clinical workflow, but the complexity can cause ineffectiveness, frustration, and errors. To address this, we believe digital solutions alone are not sufficient. Therefore, we take a human-centred design approach for AI development, and apply systems engineering methods to identify system leverage points. We demonstrate how automation enables monitoring clinical parameters, using existing non-intrusive sensor technology, resulting in more resources toward patient care. Furthermore, we provide a framework on digitization of clinical data for integration with data management.},
  language  = {en}
}