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Design Principles for (X)AI-based Patient Education Systems

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dc.contributor.authorPfeuffer, Nicolas
dc.date.accessioned2022-05-03T09:55:39Z
dc.date.available2022-05-03T09:55:39Z
dc.date.issued2021
dc.description.abstractRecently, the management of chronic diseases has advanced to a prime topic for Information Systems (IS) research and practice. With increasing capability of Information Technology, patients are empowered to engage in self-management of chronic diseases connected to promises of health benefits for the individual as well as an unburdening of clinics and economic advantages for health care systems. Nevertheless, patients must be adequately educated about risks, screening and examination options to make patient self-management effective, sustainable and profitable. In this regard, Explainable Artificial Intelligence ((X)AI)-based Patient Education Systems (PES) may be an opportunity to provide patient education in an interactive, intelligible and intelligent manner. By establishing Design Principles (DP) for the engineering of effective (X)AIbased PES, instantiating them in a system prototype and evaluating the DP with the help of general practitioners, this paper contributes to the body of knowledge in designing health IS.en
dc.identifier.doi10.18420/wifo2021-12
dc.identifier.isbn978-3-88579-713-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/38622
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartof3. Wissenschaftsforum: Digitale Transformation (WiFo21)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-319
dc.subjectPatient Education
dc.subjectPatient Adherence
dc.subjectExplainable Artificial Intelligence
dc.subjectDesign Science
dc.titleDesign Principles for (X)AI-based Patient Education Systemsen
gi.citation.endPage157
gi.citation.startPage143
gi.conference.date05. November 2021
gi.conference.locationDarmstadt
gi.conference.sessiontitleFragen und (technische) Antworten der Digitalen Transformation

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P319 - 3. Wissenschaftsforum: Digitale Transformation (WiFo21)