ArticleJMIR human factors2024
The Promise of AI for Image-Driven Medicine: Qualitative Interview Study of Radiologists' and Pathologists' Perspectives.
Article in JMIR human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ethical concerns of AI in healthcare: A systematic review of qualitative studies.Nursing ethics · 2026Pooled it
- Autonomous AI in prostate cancer: the road ahead towards clinical implementation.Abdominal radiology (New York) · 2026Review
- Anticipating Moral and Economic Considerations, Opportunities, and Potential Frictions for AI in Medical Imaging: Multistakeholder Cocreation Study.Journal of medical Internet research · 2026Article
- Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review.EClinicalMedicine · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Image-driven specialisms such as radiology and pathology are at the forefront of medical artificial intelligence (AI) innovation. Many believe that AI will lead to significant shifts in professional roles, so it is vital to investigate how professionals view the pending changes that AI innovation will initiate and incorporate their views in ongoing AI developments. Objective: Our study aimed to gain insights into the perspectives and wishes of radiologists and pathologists regarding the promise of AI. Methods: We have conducted the first qualitative interview study investigating the perspectives of both radiologists and pathologists regarding the integration of AI in their fields. The study design is in accordance with the consolidated criteria for reporting qualitative research (COREQ). Results: In total, 21 participants were interviewed for this study (7 pathologists, 10 radiologists, and 4 computer scientists). The interviews revealed a diverse range of perspectives on the impact of AI. Respondents discussed various task-specific benefits of AI; yet, both pathologists and radiologists agreed that AI had yet to live up to its hype. Overall, our study shows that AI could facilitate welcome changes in the workflows of image-driven professionals and eventually lead to better quality of care. At the same time, these professionals also admitted that many hopes and expectations for AI were unlikely to become a reality in the next decade. Conclusions: This study points to the importance of maintaining a "healthy skepticism" on the promise of AI in imaging specialisms and argues for more structural and inclusive discussions about whether AI is the right technology to solve current problems encountered in daily clinical practice.
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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.