ArticleJMIR medical education2023
Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review.
Article in JMIR medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers, 10 of them syntheses 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
169 citing papers in PubMed, 10 syntheses or guidelines pooled it.
- The impact of generative artificial intelligence tools on assessment equity for non-native English-speaking medical students: a systematic review.BMC medical education · 2026Pooled it
- Quality assurance in generative AI-mediated education: a bibliometric and scoping review.Frontiers in artificial intelligence · 2026Pooled it
- Mapping artificial intelligence in problem-based and case-based medical education: a bibliometric analysis (2019-2026).Frontiers in medicine · 2026Pooled it
- The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence.Frontiers in medicine · 2026Pooled it
- AI-generated videos in medical education: systematic review.BMJ open quality · 2025Pooled it
- Advancements in artificial intelligence transforming medical education: a comprehensive overview.Medical education online · 2025Pooled it
- Effectiveness of generative artificial intelligence-based teaching versus traditional teaching methods in medical education: a meta-analysis of randomized controlled trials.BMC medical education · 2025Pooled it
- [Medical education and artificial intelligence: perspectives and ethical challenges].Revista medica del Instituto Mexicano del Seguro Social · 2025Pooled it
- A systematic review of the impact of artificial intelligence on educational outcomes in health professions education.BMC medical education · 2025Pooled it
- Integrating large language models into prostate cancer training: evidence from comparative benchmarking and a pilot randomized trial.BMC medical education · 2026Trial
- Comparing AI chatbot simulation and peer role-play for OSCE preparation: a pilot randomized controlled trial.BMC medical education · 2025Trial
- Feasibility study of using GPT for history-taking training in medical education: a randomized clinical trial.BMC medical education · 2025Trial
- Generative AI-Assisted Progressive-Disclosure Case-Based Learning for Clinical Reasoning in Occupational Medicine: Quasi-Experimental Study.JMIR medical education · 2026Article
- Large Language Model Performance on Multistep Clinical Cases: Comparative Study Across Question and Case Levels.JMIR medical education · 2026Article
- A Multimodal AI Framework for Medical Education: Integrating Adaptive Image Retrieval, Fast Synthesis, and LLM-Based Clinical Auditing.Journal of imaging · 2026Article
- Teaching Model Context Protocol, Retrieval-Augmented Generation, and AI Agents to a Multidisciplinary Hospital Workforce: Single-Group Pre-Post Survey Study.JMIR medical education · 2026Article
- Promise, Mimicry, and Surveillance: Responsibly Integrating Artificial Intelligence With Socratic Inquiry in Medical Education.JMIR medical education · 2026Article
- Benchmark Survey on Content Development and Key Performance Indicators: A phactMI Benchmarking Survey Update.Therapeutic innovation & regulatory science · 2026Article
- The Challenges of AI Applications in Health Care: Qualitative Study.Journal of medical Internet research · 2026Article
109 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenerative artificial intelligence (AI) technologies are increasingly being utilized across various fields, with considerable interest and concern regarding their potential application in medical education. These technologies, such as Chat GPT and Bard, can generate new content and have a wide range of possible applications.
objectiveThis study aimed to synthesize the potential opportunities and limitations of generative AI in medical education. It sought to identify prevalent themes within recent literature regarding potential applications and challenges of generative AI in medical education and use these to guide future areas for exploration.
methodsWe conducted a scoping review, following the framework by Arksey and O'Malley, of English language articles published from 2022 onward that discussed generative AI in the context of medical education. A literature search was performed using PubMed, Web of Science, and Google Scholar databases. We screened articles for inclusion, extracted data from relevant studies, and completed a quantitative and qualitative synthesis of the data.
resultsThematic analysis revealed diverse potential applications for generative AI in medical education, including self-directed learning, simulation scenarios, and writing assistance. However, the literature also highlighted significant challenges, such as issues with academic integrity, data accuracy, and potential detriments to learning. Based on these themes and the current state of the literature, we propose the following 3 key areas for investigation: developing learners' skills to evaluate AI critically, rethinking assessment methodology, and studying human-AI interactions.
conclusionsThe integration of generative AI in medical education presents exciting opportunities, alongside considerable challenges. There is a need to develop new skills and competencies related to AI as well as thoughtful, nuanced approaches to examine the growing use of generative AI in medical education.
Indexed as
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.