SynthesisBritish medical bulletin2025
Physicians' required competencies in AI-assisted clinical settings: a systematic review.
Synthesis in British medical bulletin, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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.
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Who cites it
24 citing papers in PubMed.
- The Perceived Influence of AI on the Craftsmanship of Physicians: Qualitative Interview and Focus Group Study.JMIR AI · 2026Article
- Role-Differentiated AI Competencies and Curriculum Implications for Health Professions Education: Qualitative Study.JMIR medical education · 2026Article
- Artificial Intelligence in Prehospital Tele-Emergency Medicine: A Survey of Acceptance and Attitudes.Healthcare (Basel, Switzerland) · 2026Article
- Artificial intelligence needs better health systems to reduce inequalities.NPJ digital medicine · 2026Review
- Awareness, Educational Needs, and Curriculum Preferences Regarding AI and Medical Big Data Education Among Clinical Medicine Undergraduates: Cross-Sectional Survey Study.JMIR formative research · 2026Article
- AI literacy in healthcare organisations: implementing article 4 of the EU AI Act with M-SHALF.npj health systems · 2026Review
- Artificial intelligence in rheumatology and paediatric rheumatology: insights from an international survey by EMEUNET.EULAR rheumatology open · 2026Article
- Fertility care in the age of algorithms: opportunities and risks of AI and social media integration in reproductive medicine.Journal of assisted reproduction and genetics · 2026Review
- Artificial intelligence in medicine: a scoping review of the risk of deskilling and loss of expertise among physicians.ESMO real world data and digital oncology · 2026Review
- Digital health literacy in medical education: a scoping review of current challenges and development strategies.BMC medical education · 2026Article
- Independent and collaborative performance of large language models and healthcare professionals in diagnosis and triage.NPJ digital medicine · 2026Article
- Flight rules for clinical AI: lessons from aviation for human-AI collaboration in medicine.NPJ digital medicine · 2026Review
- From Agents to Governance: Essential AI Skills for Clinicians in the Large Language Model Era.Journal of medical Internet research · 2026Article
- Virtual patients and standardized patients combined training is associated with improved clinical reasoning among medical students.Frontiers in medicine · 2026Article
- From de-skilling to up-skilling: How artificial intelligence will augment the modern physician.Journal of experimental orthopaedics · 2026Review
- AI and algorithmic literacy among health workers: a scoping review through a digital health literacy lens.Frontiers in public health · 2026Article
- Preparing tomorrow's physicians for AI-driven healthcare: insights from a study on medical students', interns', and residents' knowledge, attitudes, and educational needs.Frontiers in medicine · 2026Article
- Clearing the Mist: The Distinct Roles of Transparency and Explainability for Using AI in Drug and Device Development.Pharmaceutical medicine · 2026Article
- From Bainbridge to bedside: applying automation insights to medical curriculum and assignment design in the artificial intelligence era.Korean journal of medical education · 2025Article
- Integrating artificial intelligence into medical education: a roadmap informed by a survey of faculty and students.Medical education online · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUtilizing Artificial Intelligence (AI) in clinical settings may offer significant benefits. A roadblock to the responsible implementation of medical AI is the remaining uncertainty regarding requirements for AI users at the bedside. An overview of the academic literature on human requirements for the adequate use of AI in clinical settings is therefore of significant value. SOURCES OF DATA: A systematic review of the potential implications of medical AI for the required competencies of physicians as mentioned in the academic literature. AREAS OF AGREEMENT: Our findings emphasize the importance of physicians' critical human skills, alongside the growing demand for technical and digital competencies. AREAS OF CONTROVERSY: Concrete guidance on physicians' required competencies in AI-assisted clinical settings remains ambiguous and requires further clarification and specification. Dissensus remains over whether physicians are adequately equipped to use and monitor AI in clinical settings in terms of competencies, skills and expertise, issues of ownership regarding normative guidance, and training of physicians' skills. GROWING POINTS: Our review offers a basis for subsequent further research and normative analysis on the responsible use of AI in clinical settings. AREAS TIMELY FOR DEVELOPING RESEARCH: Future research should clearly outline (i) how physicians must be(come) competent in working with AI in clinical settings, (ii) who or what should take ownership of embedding these competencies in a normative and regulatory framework, (iii) investigate conditions for achieving a reasonable amount of trust in AI, and (iv) assess the connection between trust and efficiency in patient care.
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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.