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dc.contributor.authorMalerbi, Fernando Korn
dc.contributor.authorNakayama, Luis Filipe
dc.contributor.authorGayle Dychiao, Robyn
dc.contributor.authorZago Ribeiro, Lucas
dc.contributor.authorVillanueva, Cleva
dc.contributor.authorCeli, Leo Anthony
dc.contributor.authorRegatieri, Caio Vinicius
dc.date.accessioned2024-02-09T21:59:52Z
dc.date.available2024-02-09T21:59:52Z
dc.date.issued2023-06-22
dc.identifier.issn1438-8871
dc.identifier.urihttps://hdl.handle.net/1721.1/153495
dc.description.abstractArtificial Intelligence (AI) represents a significant milestone in health care's digital transformation. However, traditional health care education and training often lack digital competencies. To promote safe and effective AI implementation, health care professionals must acquire basic knowledge of machine learning and neural networks, critical evaluation of data sets, integration within clinical workflows, bias control, and human-machine interaction in clinical settings. Additionally, they should understand the legal and ethical aspects of digital health care and the impact of AI adoption. Misconceptions and fears about AI systems could jeopardize its real-life implementation. However, there are multiple barriers to promoting electronic health literacy, including time constraints, overburdened curricula, and the shortage of capacitated professionals. To overcome these challenges, partnerships among developers, professional societies, and academia are essential. Integrating specialists from different backgrounds, including data specialists, lawyers, and social scientists, can significantly contribute to combating digital illiteracy and promoting safe AI implementation in health care.en_US
dc.language.isoen_US
dc.publisherJMIR Publications Inc.en_US
dc.relation.isversionof10.2196/43333en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceJMIR Publicationsen_US
dc.subjectHealth Informaticsen_US
dc.titleDigital Education for the Deployment of Artificial Intelligence in Health Careen_US
dc.typeArticleen_US
dc.identifier.citationMalerbi FK, Nakayama LF, Gayle Dychiao R, Zago Ribeiro L, Villanueva C, Celi LA, Regatieri CV Digital Education for the Deployment of Artificial Intelligence in Health Care J Med Internet Res 2023;25:e43333.en_US
dc.contributor.departmentHarvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2024-02-09T21:57:41Z
mit.journal.volume25en_US
mit.journal.issueJournal of Medical Internet Researchen_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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