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An evaluation of artificial intelligence assisted prostate biopsy reporting in the Articulate Pro study

Abstract:
Prospective evidence on clinical utility of AI in histopathology is limited. We conducted a prospective study across three National Health Service specialist centres in England to evaluate a commercially available AI system for assistance in prostate biopsy reporting. Of 1613 cases, 1049 were reported with AI-assistance. Endpoints evaluated diagnostic impact, clinical impact and workflow. Staged AI assistance (second-read) prompted case review and changed the initial diagnosis or Grade Group of 21/386(5.4%) patients, 5 of these (1.3%) potentially affecting clinical management. AI-assisted workflows showed significantly reduced mean turnaround time with concurrent-read compared to unassisted-read by 30.1 h (p < 0.0001) at one site with significant reductions in cases requiring immunohistochemistry in all sites (Odds Ratios 0.50,0.43,0.33, p < 0.0001, p = 0.01, p = 0.001). This first prospective, multi-centric evaluation demonstrates AI can enhance diagnostic accuracy, shorten turnaround times and reduce unnecessary testing. Scaled across the NHS, such improvements could improve patient care, deliver faster diagnoses and optimise laboratory efficiency, supporting adoption.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41746-026-02592-8

Authors

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-1542-5357
More by this author
Institution:
University of Oxford
Role:
Author
ORCID:
0000-0001-6344-9081
More by this author
Institution:
University of Oxford
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0003-1479-3251


Publisher:
Nature Research
Journal:
npj Digital Medicine More from this journal
Publication date:
2026-05-22
DOI:
EISSN:
2398-6352
ISSN:
2398-6352


Language:
English
Keywords:
Pubs id:
2423131
Local pid:
pubs:2423131
Source identifiers:
W7162131192
Deposit date:
2026-06-23
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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