ArticleJournal of clinical pathology2023
Survey of liver pathologists to assess attitudes towards digital pathology and artificial intelligence.
Article in Journal of clinical pathology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- Perceptions of digital pathology among healthcare workers in pathology.Journal of pathology informatics · 2026Article
- Automating liver biopsy segmentation with a robust, open-source tool for pathology research: the HOTSPoT model.NPJ digital medicine · 2025Article
- Entropy and expertise: assessing changes in pathologists' language over time using the UK Liver Pathology External Quality Assessment scheme.The journal of pathology. Clinical research · 2025Article
- Deep learning helps discriminate between autoimmune hepatitis and primary biliary cholangitis.JHEP reports : innovation in hepatology · 2025Article
- Human-machine interaction in computational cancer pathology.ESMO real world data and digital oncology · 2024Review
- Improving HCC Prognostic Models after Liver Resection by AI-Extracted Tissue Fiber Framework Analytics.Cancers · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 11 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsA 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).
methodsThe 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.
resultsForty-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.
conclusionsThis 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.