Perceived risk and mitigation of AI-supported clinical decision-making among radiologists: an exploratory study

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dc.contributor.authorAlshamrani, Abdullatif
dc.contributor.authorTreacy, Stephen
dc.contributor.authorRowan, Wendy
dc.contributor.authorO’Flaherty, Brian
dc.contributor.authorEngland, Andrew
dc.contributor.funderKingdom of Saudi Arabia
dc.date.accessioned2026-07-10T09:50:01Z
dc.date.available2026-07-10T09:50:01Z
dc.date.issued2026-05-19
dc.description.abstractArtificial intelligence (AI) promises to revolutionise radiology practices. However, the AI implementation to support clinical decision-making relies on radiologists’ understanding of associated risks, as it has a pivotal role in providing outstanding healthcare outcome delivery. This study aims to explore the perception of risks related to AI and how to mitigate them from radiologists’ perspective via semi-structured interviews for more in-depth information. Preliminary findings indicate that most of the literature for the most part focused on attitudes and beliefs. As a work in progress, it is significant to bridge gaps in terms of the limited of empirical studies on risk perceptions of AI and insufficient theoretical grounding. This Research-In-Progress paper has provided a research framework, methodology and anticipated contributions while also seeking insightful critique to strengthen the research argument and its significance.en
dc.description.versionPublished Version
dc.format.extent5
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid2664010
dc.identifier.authororcidAlshamrani, Abdullatif
dc.identifier.authororcidTreacy, Stephen§0000-0002-3980-5565
dc.identifier.authororcidRowan, Wendy§0000-0001-8941-1508
dc.identifier.authororcidO’Flaherty, Brian
dc.identifier.authororcidEngland, Andrew§0000-0001-6333-7776
dc.identifier.citationAlshamrani, A, Treacy, S, Rowan, W, O’Flaherty, B & England, A 2026, 'Perceived risk and mitigation of AI-supported clinical decision-making among radiologists: an exploratory study', Journal of Decision Systems, vol. 35, no. 1, 2664010, pp. 1-5. https://doi.org/10.1080/12460125.2026.2664010
dc.identifier.doi10.1080/12460125.2026.2664010
dc.identifier.endpage5
dc.identifier.issn1246-0125
dc.identifier.issued1
dc.identifier.journaltitleJournal of Decision Systems
dc.identifier.otherORCID: /0000-0001-6333-7776/work/220336660
dc.identifier.otherORCID: /0000-0002-3980-5565/work/220337209
dc.identifier.otherORCID: /0000-0001-8941-1508/work/220337338
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/10468/19047
dc.identifier.volume35
dc.language.isoen
dc.publisherTaylor and Francis Ltd.
dc.relation.urihttps://www.scopus.com/pages/publications/105039451880
dc.rights© 2026, the Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allowthe posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
dc.rights.accessrightsopen access
dc.rights.licensenameAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.statusPeer reviewed
dc.subjectArtificial intelligence
dc.subjectBehaviour
dc.subjectClinical decision making
dc.subjectMitigation
dc.subjectPerception of risk
dc.subjectRadiologists
dc.subjectTEO Framework
dc.subject[CUBS]
dc.subject[Medicine]
dc.titlePerceived risk and mitigation of AI-supported clinical decision-making among radiologists: an exploratory studyen
dc.typeArticle (peer-reviewed)
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