ArticleBJUI compass2025
Exploring patient and clinician opinions, perspectives and acceptance of the use of artificial intelligence in the histological diagnosis of prostate cancer.
Article in BJUI compass, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- An evaluation of artificial intelligence assisted prostate biopsy reporting in the Articulate Pro study.NPJ digital medicine · 2026Article
- Exploring patient and clinician opinions, perspectives and acceptance of the use of artificial intelligence in the histological diagnosis of prostate cancer.BJUI compass · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study aims to explore the opinions and attitudes of patients and clinicians regarding the use of artificial intelligence (AI) in the diagnosis of prostate biopsies, with a focus on acceptance and trust in the use of AI, and factors that may impact this. Subjects and methods: Surveys were sent to patient members of UK-based prostate cancer support groups and to a group of clinicians managing patients with prostate cancer (or suspected prostate cancer). Results: Of 130 patient respondents, 94% expressed acceptance of AI assistance in the diagnosis of prostate biopsies when a pathologist retains responsibility for the final diagnosis, but regard it as the responsibility of the pathologist to decide whether AI is used in this setting. Similar responses were noted among the nine clinician respondents. Regarding factors with potential impact on acceptance of AI, an understanding of how the AI was tested and its performance in comparison with a pathologist was considered to be more important than how the technology was developed, and half (51%) of patients suggested that access to additional information might impact their acceptance of AI. Conclusion: Understanding the perspectives of stakeholders is key to the successful clinical implementation of AI in the histological diagnosis of prostate biopsies. Our study shows a high level of acceptance of AI for the diagnosis of prostate biopsies among patients if a pathologist retains oversight of the diagnosis and the decision as to when AI is used. Furthermore, it suggests similar levels of acceptance among clinicians. Our study provides insight into areas for educational focus to enhance understanding of AI in this setting.
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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.