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dc.contributor.authorTrocin, Cristina
dc.contributor.authorMikalef, Patrick
dc.contributor.authorPapamitsiou, Zacharoula
dc.contributor.authorConboy, Kieran
dc.date.accessioned2023-01-26T07:33:53Z
dc.date.available2023-01-26T07:33:53Z
dc.date.created2021-12-10T15:10:34Z
dc.date.issued2021
dc.identifier.citationInformation Systems Frontiers. 2021, .en_US
dc.identifier.issn1387-3326
dc.identifier.urihttps://hdl.handle.net/11250/3046433
dc.description.abstractResponsible AI is concerned with the design, implementation and use of ethical, transparent, and accountable AI technology in order to reduce biases, promote fairness, equality, and to help facilitate interpretability and explainability of outcomes, which are particularly pertinent in a healthcare context. However, the extant literature on health AI reveals significant issues regarding each of the areas of responsible AI, posing moral and ethical consequences. This is particularly concerning in a health context where lives are at stake and where there are significant sensitivities that are not as pertinent in other domains outside of health. This calls for a comprehensive analysis of health AI using responsible AI concepts as a structural lens. A systematic literature review supported our data collection and sampling procedure, the corresponding analysis, and extraction of research themes helped us provide an evidence-based foundation. We contribute with a systematic description and explanation of the intellectual structure of Responsible AI in digital health and develop an agenda for future research.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleResponsible AI for Digital Health: a Synthesis and a Research Agendaen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber19en_US
dc.source.journalInformation Systems Frontiersen_US
dc.identifier.doi10.1007/s10796-021-10146-4
dc.identifier.cristin1967185
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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