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dc.rights.licenseopenen_US
dc.contributor.authorCOULIBALY, Daouda
dc.contributor.authorBAYANI, Azadeh
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorSYLLA, Bry
dc.contributor.authorMOTULSKY, Aude
dc.contributor.authorNIKIEMA, Jean Noel
dc.contributor.authorBOSSON-RIEUTORT, Delphine
dc.date.accessioned2025-05-07T08:52:16Z
dc.date.available2025-05-07T08:52:16Z
dc.date.issued2025-02-18
dc.identifier.issn2044-6055en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/206570
dc.description.abstractEnIntroduction Empirical data on the barriers limiting artificial intelligence (AI)'s impact on healthcare are scarce, particularly within the Canadian context. This study aims to address this gap by conducting a scoping review to identify and evaluate AI algorithms developed by researchers affiliated with Canadian institutions for patient triage, diagnosis and care management. The goal is to identify characteristics in the developed AI algorithms that can be leveraged for a better impact.Methods and analysis A scoping review will be conducted following the JBI Methodology for Scoping Reviews and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. Relevant literature will be identified through comprehensive searches of MEDLINE (PubMed), CINAHL (EBSCO) and Web of Science (Clarivate) databases, combining keywords related to AI, clinical management and the Canadian context. Studies published after 2014, in English or French, that discuss AI algorithms developed for patient triage, diagnosis or care management by researchers affiliated with Canadian institutions will be included. Data from the selected articles will be extracted and analysed descriptively, and findings will be presented in tabular form accompanied by a narrative summary.Ethics and dissemination Ethical approval is not required for this study as it involves the review of publicly available literature. The scoping review is expected to be completed by November 2025. The findings will be disseminated through publications in peer-reviewed journals and presentations at conferences focused on AI and healthcare practice.
dc.language.isoENen_US
dc.rightsAttribution-NonCommercial 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/us/*
dc.subject.enArtificial Intelligence
dc.subject.enClinical Decision-Making
dc.subject.enDelivery of Healthcare
dc.subject.enIntegrated
dc.subject.enReview
dc.title.enIdentifying key characteristics of developed artificial intelligence algorithms to achieve meaningful impact on Canadian healthcare: a scoping review protocol
dc.title.alternativeBMJ Openen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1136/bmjopen-2024-094908en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed39965945en_US
bordeaux.journalBMJ Openen_US
bordeaux.pagee094908en_US
bordeaux.volume15en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issue2en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.teamAHEAD_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-05059078
hal.version1
hal.date.transferred2025-05-07T08:52:19Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
dc.rights.ccPas de Licence CCen_US
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