ArticleAdvances in medical education and practice2025
Artificial Intelligence in Medical Education: Promise, Pitfalls, and Practical Pathways.
Article in Advances in medical education and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- [Medical education and artificial intelligence: perspectives and ethical challenges].Revista medica del Instituto Mexicano del Seguro Social · 2025Pooled it
- Artificial Intelligence Readiness in Emergency Medicine: Expert Consensus Opinion for Preparing the Workforce.Journal of the American College of Emergency Physicians open · 2026Article
- AI literacy among healthcare professionals and students in the Americas.Lancet regional health. Americas · 2026Review
- Addressing Clinician-Educator Hesitancy Toward Artificial Intelligence Through a Peer-Led Instructional Design.Cureus · 2026Article
- Educational Frameworks for Diagnostic Decision-Making in AI-Enhanced Head and Neck Pathology.Head and neck pathology · 2026Review
- Blending Artificial Intelligence with Expertise: A Comparative Study of Concept Maps in Anatomy Education.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026Article
- Article
- Quality of ChatGPT-Generated Responses to Common Patient Questions About Peripheral Nerve Stimulation: A Cross-Sectional Study.Clinics and practice · 2026Article
- Artificial intelligence in veterinary education: self-perceived knowledge, use, and attitudes among veterinary students in Spain and Portugal.Frontiers in veterinary science · 2026Article
- Current Landscape of Curriculum Development and Implementation in Medical Artificial Intelligence: A Scoping Review.Journal of multidisciplinary healthcare · 2026Review
- AI literacy in undergraduate medical education: a competency-based interpretive framework for curriculum and assessment.Frontiers in medicine · 2026Review
- Twelve tips for developing and implementing AI curriculum for undergraduate medical education.Medical education online · 2025Review
- From Caution to Readiness: The Case for Responsible AI in Pediatric Oncology Education.Journal of cancer education : the official journal of the American Association for Cancer Education · 2025Article
- 10 tips for clinical educators in designing and delivering learning experiences to improve clinical reasoning for medical students.MedEdPublish (2016) · 2025Article
- Artificial intelligence in pediatric Wilms tumor imaging: diagnostic performance and the need for clinical oversight.Jornal brasileiro de nefrologiaArticle
- Artificial Intelligence in Healthcare: Awareness, Perceptions, and Future Perspectives of Palestinian Medical Students and Physicians.Journal of medical education and curricular developmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is transforming healthcare, yet its integration into medical education remains limited. As AI-powered tools increasingly assist with diagnostics, administrative tasks, and clinical decision-making, future doctors must have the knowledge and skills to use them effectively. This article explores the role of AI in medical education, highlighting its potential to enhance efficiency, improve patient care, and foster innovation while addressing ethical and safety concerns. The widespread adoption of AI presents both opportunities and challenges. While AI-driven transcription tools reduce administrative burdens and machine learning algorithms enhance diagnostic accuracy, the risks of over-reliance, algorithmic bias, and patient data security remain critical concerns. To navigate these complexities, medical schools must incorporate AI-focused training into their curricula, ensuring graduates can critically assess and safely apply AI technologies in clinical practice. However, AI should not be seen as the only solution; non-technological improvements to clinical workflows must also be considered in parallel. This article proposes practical solutions, including optional AI modules, hands-on training with AI-powered diagnostic tools, and interdisciplinary collaboration through innovation laboratories. By embedding AI education into medical training, institutions can prepare students for a rapidly evolving healthcare landscape, ensuring AI is a tool for improved patient outcomes, not a source of unintended harm. As AI reshapes medicine, equipping future doctors with the skills to use it responsibly is essential for fostering a healthcare system that is efficient, ethical, and patient-centred.
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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.