ArticleJMIR medical education2023
The Advent of Generative Language Models in Medical Education.
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 79 papers, 5 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
79 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Artificial intelligence applications in surgical education and training: a systematic 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 impact of generative AI on health professional education: A systematic review in the context of student learning.Medical education · 2025Pooled it
- The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review.BMC oral health · 2025Pooled it
- A systematic review of the impact of artificial intelligence on educational outcomes in health professions education.BMC medical education · 2025Pooled it
- Integrating ChatGPT in Orthopedic Education for Medical Undergraduates: Randomized Controlled Trial.Journal of medical Internet research · 2024Trial
- The hidden patterns of alignment: exploring variability between generative AI and human.Medical education online · 2026Article
- Generative Language Models in Medical Education: From Advent to Entrustment.JMIR medical education · 2026Article
- Embracing Large Language Models for Medical Applications, Part II: Building a Framework for Clinical Stewardship.Cureus · 2026Article
- Principles for medical students' responsible use of generative AI: a student-partnered Delphi study.BMC medical ethics · 2026Article
- From traditional classroom to AI-enhanced flipped classroom: a three-year pedagogical evolution for international students in pharmacology.BMC medical education · 2026Article
- The application of large language models in orthopedic postgraduate education: potentials, challenges, and future prospects.Journal of orthopaedic surgery and research · 2026Review
- Artificial Intelligence in Medical Education: Transformative Potential, Current Applications, and Future Implications.JMIR medical education · 2026Article
- Assessment of large language models in musculoskeletal radiological anatomy: A comparative study with radiologists.Joint diseases and related surgery · 2026Article
- Enhancing Medical Education: The Role of Artificial Intelligence Tools in the Teaching-Learning Process.Advances in medical education and practice · 2026Review
- 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
- Generative AI in psychiatric education: balancing risks and benefits for responsible integration.Frontiers in psychiatry · 2026Article
- Application of an iterative generative AI-augmented teaching model in medical immunology education.Frontiers in artificial intelligence · 2026Article
- Incorporating Generative AI Into a Health Informatics Curriculum to Build 21st Century Competencies: Multisite Pre-Post Study.JMIR medical informatics · 2025Article
- Ten tips to harnessing generative AI for high-quality MCQS in medical education assessment.Medical education online · 2025Article
19 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) and generative language models (GLMs) present significant opportunities for enhancing medical education, including the provision of realistic simulations, digital patients, personalized feedback, evaluation methods, and the elimination of language barriers. These advanced technologies can facilitate immersive learning environments and enhance medical students' educational outcomes. However, ensuring content quality, addressing biases, and managing ethical and legal concerns present obstacles. To mitigate these challenges, it is necessary to evaluate the accuracy and relevance of AI-generated content, address potential biases, and develop guidelines and policies governing the use of AI-generated content in medical education. Collaboration among educators, researchers, and practitioners is essential for developing best practices, guidelines, and transparent AI models that encourage the ethical and responsible use of GLMs and AI in medical education. By sharing information about the data used for training, obstacles encountered, and evaluation methods, developers can increase their credibility and trustworthiness within the medical community. In order to realize the full potential of AI and GLMs in medical education while mitigating potential risks and obstacles, ongoing research and interdisciplinary collaboration are necessary. By collaborating, medical professionals can ensure that these technologies are effectively and responsibly integrated, contributing to enhanced learning experiences and patient care.
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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.