ReviewNPJ digital medicine2025
Situating governance and regulatory concerns for generative artificial intelligence and large language models in medical education.
Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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
26 citing papers in PubMed.
- Application of DeepSeek-based AI teaching assistant in teaching anesthesiology theories.BMC medical education · 2025Trial
- DEGRO consensus framework for undergraduate radiation therapy teaching in Germany: a white paper with integrated guidance on artificial intelligence in medical education.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- AI-Mediated Assessment of Continuing Medical Education: The Case-based Learning Intelligence Credit System (CLICS) Framework.JMIR medical education · 2026Article
- Large Language Model Performance on Multistep Clinical Cases: Comparative Study Across Question and Case Levels.JMIR medical education · 2026Article
- Benchmarking large language models for de-identification of electronic health record notes.BMJ health & care informatics · 2026Article
- A Large Language Model-Powered Multiagent Framework Emulating Standardized Patients in Clinical Communication Skills Training: Development and Evaluation Study.Journal of medical Internet research · 2026Article
- Generative AI's Impact on the Mental Health of Medical Students: Scenario Analysis.JMIR medical education · 2026Article
- Clinical AI is Not (Yet) Trustworthy-But It Could Be.Journal of medical Internet research · 2026Article
- Bias, representation, and clinical fidelity in AI-generated images for medical education: a systematic literature review.NPJ digital medicine · 2026Article
- Postgraduate General Practice Training Under Early Clinical Responsibility: A Narrative Review on System-Based Supervision and the Supportive Role of Artificial Intelligence.Healthcare (Basel, Switzerland) · 2026Review
- Preparedness for generative AI adoption among Chinese cancer survivors: a multi-center cross-sectional survey study.Frontiers in public health · 2026Article
- Generative Artificial Intelligence in Health Informatics Education: A Qualitative Exploration of Student Engagement, Perceived Educational Implications, and Ethical Considerations.Advances in medical education and practice · 2026Article
- A primer on artificial intelligence for palliative care educators.Palliative care and social practice · 2026Review
- Transforming surgical ward rounds: constructivist pedagogy, structured models, and intelligent technologies.Frontiers in medicine · 2026Review
- Performance of large language model in cross-specialty medical scenarios.Journal of translational medicine · 2025Article
- Assessing LLM-generated vs. expert-created clinical anatomy MCQs: a student perception-based comparative study in medical education.Medical education online · 2025Article
- Multimodal analysis of whole slide images in colorectal cancer.NPJ digital medicine · 2025Article
- Article
- Technologies, opportunities, challenges, and future directions for integrating generative artificial intelligence into medical education: a narrative review.Ewha medical journal · 2025Article
- Reflection and Experimental Rigor Are Our AiMS: A New Metacognitive Framework for Experimental Design.eNeuro · 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
Generative artificial intelligence (GenAI) and large language models represent gains in educational efficiency and personalisation of learning. These are balanced against the considerations of the learning process, authentic assessment, and academic integrity. A pedagogical approach helps situate these concerns, and informs various types of governance and regulatory approaches. In this review we identify current and emerging issues regarding GenAI in medical education including pedagogical considerations, emerging roles, and trustworthiness. Potential measures to address specific regulatory concerns are explored.
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.