ArticleJMIR medical education2023
ChatGPT Interactive Medical Simulations for Early Clinical Education: Case Study.
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 57 papers.
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Who cites it
57 citing papers in PubMed.
- Large language models improve clinical decision making of medical students through patient simulation and structured feedback: a randomized controlled trial.BMC medical education · 2024Trial
- Towards scalable psychological first aid training: an autoethnographic exploration of the potential of large language models in simulation-based learning.European journal of psychotraumatology · 2026Article
- LLM-Based Psychiatric Interview Simulation: Technical Development and Pilot Expert-Based Content Validation of a Voice Prototype.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026Article
- AI integration in healthcare simulation debriefing: support or substitute?Advances in simulation (London, England) · 2026Article
- Reimagining pharmacology education.Pharmacological reviews · 2026Review
- Review
- Article
- The new wave of generative artificial intelligence in medical education.Korean journal of medical education · 2026Article
- Incorporating Artificial Intelligence in Qualitative Research: Exploring the Role of ChatGPT in Thematic Analysis.Medical science educator · 2026Article
- Artificial intelligence based resuscitation simulation: a pilot study of a novel approach to team leadership training.BMC medical education · 2026Article
- Orthopedic Residency Training Reform in Iran: A Competency-Based Approach.The archives of bone and joint surgery · 2026Article
- Evaluation of a Hybrid Case-Based Learning and Small-Group Teaching Model Using Artificial Intelligence-Assisted Case Generation: An Innovative Dental Education Study.Advances in medical education and practice · 2026Article
- Artificial Intelligence in cardiopulmonary resuscitation training - A scoping review.Resuscitation plus · 2026Review
- An Organized Approach to Using Large Language Models for Medical Information.The western journal of emergency medicine · 2025Article
- Empowering standardized residency training in China through large language models: problem analysis and solutions.Annals of medicine · 2025Article
- Artificial intelligence in undergraduate medical education: an updated scoping review.BMC medical education · 2025Article
- The AI-powered pathologist: A global survey mapping initial trends in AI adoption and outlook.Journal of pathology informatics · 2025Article
- Applications, Challenges, and Prospects of Generative Artificial Intelligence Empowering Medical Education: Scoping Review.JMIR medical education · 2025Article
- ChatGPT in Medical Education: Bibliometric and Visual Analysis.JMIR medical education · 2025Review
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe transition to clinical clerkships can be difficult for medical students, as it requires the synthesis and application of preclinical information into diagnostic and therapeutic decisions. ChatGPT-a generative language model with many medical applications due to its creativity, memory, and accuracy-can help students in this transition.
objectiveThis paper models ChatGPT 3.5's ability to perform interactive clinical simulations and shows this tool's benefit to medical education.
methodsSimulation starting prompts were refined using ChatGPT 3.5 in Google Chrome. Starting prompts were selected based on assessment format, stepwise progression of simulation events and questions, free-response question type, responsiveness to user inputs, postscenario feedback, and medical accuracy of the feedback. The chosen scenarios were advanced cardiac life support and medical intensive care (for sepsis and pneumonia).
resultsTwo starting prompts were chosen. Prompt 1 was developed through 3 test simulations and used successfully in 2 simulations. Prompt 2 was developed through 10 additional test simulations and used successfully in 1 simulation.
conclusionsChatGPT is capable of creating simulations for early clinical education. These simulations let students practice novel parts of the clinical curriculum, such as forming independent diagnostic and therapeutic impressions over an entire patient encounter. Furthermore, the simulations can adapt to user inputs in a way that replicates real life more accurately than premade question bank clinical vignettes. Finally, ChatGPT can create potentially unlimited free simulations with specific feedback, which increases access for medical students with lower socioeconomic status and underresourced medical schools. However, no tool is perfect, and ChatGPT is no exception; there are concerns about simulation accuracy and replicability that need to be addressed to further optimize ChatGPT's performance as an educational resource.
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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.