ArticleJMIR medical education2024
Embracing ChatGPT for Medical Education: Exploring Its Impact on Doctors and Medical Students.
Article in JMIR medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 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
54 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Application of deep machine learning in dental education: a systematic review of effectiveness in dental students' teaching learning outcomes.Evidence-based dentistry · 2026Pooled it
- Application of AI-Generated Content in Medical Education: Systematic Review of the Impact on Critical Thinking Abilities of Medical Students.JMIR medical education · 2026Pooled it
- The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled 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
- Performance of ChatGPT Across Different Versions in Medical Licensing Examinations Worldwide: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Feasibility study of using GPT for history-taking training in medical education: a randomized clinical trial.BMC medical education · 2025Trial
- Implementation and evaluation of an optimized surgical clerkship teaching model utilizing ChatGPT.BMC medical education · 2024Trial
- Integrating ChatGPT into knowledge-retrieval tutorials in undergraduate medical education: a prospective evaluation of higher-order learning and feasibility.Medical education online · 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
- Augmenting medical data interpretation with Large Language Models (LLMs): a comparative analysis of patient empowerment, information processing, and technology acceptance.BMC medical informatics and decision making · 2026Article
- Effectiveness of Artificial Intelligence-Assisted Peer Teaching in Orthopedic Clinical Education: Historical Cohort Study.JMIR medical education · 2026Article
- Exploration of an artificial intelligence-supported training mechanism for teaching competence development in graduate students of prosthodontics.BMC medical education · 2026Article
- Evaluation of ChatGPT-4o in oral and maxillofacial surgery examinations: a comparative study of performance on U.S. dental decks and chinese dental licensing examination practice questions.BMC oral health · 2026Article
- The application of large language models in orthopedic postgraduate education: potentials, challenges, and future prospects.Journal of orthopaedic surgery and research · 2026Review
- Assessing the accuracy and educational value of ChatGPT-generated content for core topics in cardiology: a descriptive analysis at Selçuk University Cardiology Clinic.BMC medical education · 2026Article
- Pilot Study Comparing Emergency Physician and Artificial Intelligence-supported Interpretations of Electrocardiograms.The western journal of emergency medicine · 2026Article
- Review
- AI-Driven Objective Structured Clinical Examination Generation in Digital Health Education: Comparative Analysis of Three GPT-4o Configurations.JMIR medical education · 2026Article
- Differences and Trends of Artificial Intelligence in Medical Education: A Comparative Bibliometric Analysis Between China and the International Community.Advances in medical education and practice · 2026Article
- Large language models in emergency medicine education: opportunities, challenges, and implementation pathways.Frontiers in public health · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ChatGPT (OpenAI), a cutting-edge natural language processing model, holds immense promise for revolutionizing medical education. With its remarkable performance in language-related tasks, ChatGPT offers personalized and efficient learning experiences for medical students and doctors. Through training, it enhances clinical reasoning and decision-making skills, leading to improved case analysis and diagnosis. The model facilitates simulated dialogues, intelligent tutoring, and automated question-answering, enabling the practical application of medical knowledge. However, integrating ChatGPT into medical education raises ethical and legal concerns. Safeguarding patient data and adhering to data protection regulations are critical. Transparent communication with students, physicians, and patients is essential to ensure their understanding of the technology's purpose and implications, as well as the potential risks and benefits. Maintaining a balance between personalized learning and face-to-face interactions is crucial to avoid hindering critical thinking and communication skills. Despite challenges, ChatGPT offers transformative opportunities. Integrating it with problem-based learning, team-based learning, and case-based learning methodologies can further enhance medical education. With proper regulation and supervision, ChatGPT can contribute to a well-rounded learning environment, nurturing skilled and knowledgeable medical professionals ready to tackle health care challenges. By emphasizing ethical considerations and human-centric approaches, ChatGPT's potential can be fully harnessed in medical education, benefiting both students and patients alike.
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.