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Lookup NU author(s): Professor Alastair BurtORCiD, Professor Dina Tiniakos
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ. AIMS: A survey of members of the UK Liver Pathology Group (UKLPG) was conducted, comprising consultant histopathologists from across the UK who report liver specimens and participate in the UK National Liver Pathology External Quality Assurance scheme. The aim of this study was to understand attitudes and priorities of liver pathologists towards digital pathology and artificial intelligence (AI). METHODS: The survey was distributed to all full consultant members of the UKLPG via email. This comprised 50 questions, with 48 multiple choice questions and 2 free-text questions at the end, covering a range of topics and concepts pertaining to the use of digital pathology and AI in liver disease. RESULTS: Forty-two consultant histopathologists completed the survey, representing 36% of fully registered members of the UKLPG (42/116). Questions examining digital pathology showed respondents agreed with the utility of digital pathology for primary diagnosis 83% (34/41), second opinions 90% (37/41), research 85% (35/41) and training and education 95% (39/41). Fatty liver diseases were an area of demand for AI tools with 80% in agreement (33/41), followed by neoplastic liver diseases with 59% in agreement (24/41). Participants were concerned about AI development without pathologist involvement 73% (30/41), however, 63% (26/41) disagreed when asked whether AI would replace pathologists. CONCLUSIONS: This study outlines current interest, priorities for research and concerns around digital pathology and AI for liver pathologists. The majority of UK liver pathologists are in favour of the application of digital pathology and AI in clinical practice, research and education.
Author(s): McGenity C, Randell R, Bellamy C, Burt A, Cratchley A, Goldin R, Hubscher SG, Neil DAH, Quaglia A, Tiniakos D, Wyatt J, Treanor D
Publication type: Article
Publication status: Published
Journal: Journal of Clinical Pathology
Year: 2024
Volume: 77
Issue: 1
Pages: 27-33
Print publication date: 01/01/2024
Online publication date: 01/04/2023
Acceptance date: 24/11/2022
Date deposited: 03/01/2024
ISSN (print): 0021-9746
ISSN (electronic): 1472-4146
Publisher: BMJ Publishing Group
URL: https://doi.org/10.1136/jcp-2022-208614
DOI: 10.1136/jcp-2022-208614
Data Access Statement: All data relevant to the study are included in the article or uploaded as online supplemental information.
PubMed id: 36599660
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