Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy

McGenity, C., Clarke, E.L., Jennings, C. et al. (5 more authors) (2024) Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy. npj Digital Medicine, 7. 114. ISSN 2398-6352

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Item Type: Article
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© The Author(s) 2024. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Dates:
  • Published (online): 4 May 2024
  • Accepted: 12 April 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cancer and Pathology (LICAP)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Research (LIMR) > Division of Pathology and Data Analytics
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Clinical Trials Research (LICTR) (Leeds)
Funding Information:
Funder
Grant number
Alan Turing Institute
No Ext Ref
MRC (Medical Research Council)
MR/S001530/1
Depositing User: Symplectic Publications
Date Deposited: 05 Jul 2024 13:37
Last Modified: 05 Jul 2024 13:37
Status: Published online
Publisher: Nature Research
Identification Number: 10.1038/s41746-024-01106-8
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Sustainable Development Goals:
  • Sustainable Development Goals: Goal 3: Good Health and Well-Being
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