Journal article : Review
Stakeholder perspectives of clinical artificial intelligence implementation: systematic review of qualitative evidence
- Abstract:
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Background: The rhetoric surrounding clinical artificial intelligence (AI) often exaggerates its effect on real-world care. Limited understanding of the factors that influence its implementation can perpetuate this.
Objective: In this qualitative systematic review, we aimed to identify key stakeholders, consolidate their perspectives on clinical AI implementation, and characterize the evidence gaps that future qualitative research should target.
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 469.4KB, Terms of use)
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- Publisher copy:
- 10.2196/39742
Authors
+ Medical Research Council
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- Funder identifier:
- https://ror.org/03x94j517
- Grant:
- MR/T019050/1
- Publisher:
- JMIR Publications
- Journal:
- Journal of Medical Internet Research More from this journal
- Volume:
- 25
- Article number:
- e39742
- Publication date:
- 2023-01-10
- Acceptance date:
- 2022-11-30
- DOI:
- EISSN:
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1438-8871
- Pmid:
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36626192
- Language:
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English
- Keywords:
- Subtype:
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Review
- Pubs id:
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1322091
- Local pid:
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pubs:1322091
- Deposit date:
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2025-06-23
- ARK identifier:
Terms of use
- Copyright holder:
- Hogg et al.
- Copyright date:
- 2023
- Rights statement:
- © Henry David Jeffry Hogg, Mohaimen Al-Zubaidy, Technology Enhanced Macular Services Study Reference Group, James Talks, Alastair K Denniston, Christopher J Kelly, Johann Malawana, Chrysanthi Papoutsi, Marion Dawn Teare, Pearse A Keane, Fiona R Beyer, Gregory Maniatopoulos. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.01.2023. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
- Licence:
- CC Attribution (CC BY)
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