Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59435, first published .
Application of Large Language Models in Medical Training Evaluation—Using ChatGPT as a Standardized Patient: Multimetric Assessment

Application of Large Language Models in Medical Training Evaluation—Using ChatGPT as a Standardized Patient: Multimetric Assessment

Application of Large Language Models in Medical Training Evaluation—Using ChatGPT as a Standardized Patient: Multimetric Assessment

Journals

  1. Öncü S, Torun F, Ülkü H. AI-powered standardised patients: evaluating ChatGPT-4o’s impact on clinical case management in intern physicians. BMC Medical Education 2025;25(1) View
  2. Caballero Mateos A, Cañadas de la Fuente G, Gros B. Paradigm Shift in Inflammatory Bowel Disease Management: Precision Medicine, Artificial Intelligence, and Emerging Therapies. Journal of Clinical Medicine 2025;14(5):1536 View
  3. Deichsel A, Öttl F, Pawelczyk J, Usov L, Haffer H. Künstliche Intelligenz in der chirurgischen Weiterbildung. Die Unfallchirurgie 2025;128(8):571 View
  4. Bolgova O, Ganguly P, Mavrych V. Comparative analysis of LLMs performance in medical embryology: A cross‐platform study of ChatGPT, Claude, Gemini, and Copilot. Anatomical Sciences Education 2025;18(7):718 View
  5. Urda-Cîmpean A, Leucuța D, Drugan C, Duțu A, Călinici T, Drugan T. Assessing the Accuracy of Diagnostic Capabilities of Large Language Models. Diagnostics 2025;15(13):1657 View
  6. Cao Y, Peng L, Zhang Y, Yang C. Retrieve Then Rerank: An End‐to‐End Learning Paradigm for Biomedical Entity Linking. Journal of Evidence-Based Medicine 2025;18(3) View
  7. Cheng Y, Zhu L. A review of ChatGPT in medical education: exploring advantages and limitations. International Journal of Surgery 2025;111(7):4586 View
  8. Liu Y, Shi C, Wu L, Lin X, Chen X, Zhu Y, Tan H, Zhang W. Development and Validation of a Large Language Model–Based System for Medical History-Taking Training: Prospective Multicase Study on Evaluation Stability, Human-AI Consistency, and Transparency. JMIR Medical Education 2025;11:e73419 View
  9. Ting P, Wolffsohn J. Artificial intelligence-driven patient history and symptoms combined with slit-lamp eye simulation for enhancing the clinical training of students. Clinical and Experimental Optometry 2025:1 View
  10. Zhang Y, Xie X, Xu Q. ChatGPT in Medical Education: Bibliometric and Visual Analysis. JMIR Medical Education 2025;11:e72356 View
  11. Jo Y, Lee M, Yang H. Large Language Model-Based Virtual Patient Simulations in Medical and Nursing Education: A Review. Applied Sciences 2025;15(22):11917 View
  12. Zeng J, Qi W, Shen S, Liu X, Li S, Wang B, Dong C, Zhu X, Shi Y, Lou X, Wang B, Yao J, Jiang G, Zhang Q, Cao S. Embracing the Future of Medical Education With Large Language Model–Based Virtual Patients: Scoping Review. Journal of Medical Internet Research 2025;27:e79091 View
  13. Cheng W, Hu Z, Yu H. A bibliometric analysis of artificial intelligence in medical education (2015–2025). Medicine 2025;104(46):e45684 View
  14. Wang Y, Chang C, Shi W, Liu H, Huang X, Jiao Y. How AI Is Transforming Medical Education: Bibliometric Analysis. JMIR Medical Education 2025;11:e75911 View
  15. Chang L, Hung L, Liu T, Huang C, Lin H, Liao L. Relationships between ChatGPT use with self-directed learning and critical thinking among school and university nurses in Taiwan. BMC Nursing 2025;24(1) View
  16. Elhilali A, Ngo A, Reichenpfader D, Denecke K. Large language model-based patient simulation to foster communication skills in healthcare professionals: User-centered development and usability study (Preprint). JMIR Medical Education 2025 View

Conference Proceedings

  1. Preiß N, Westner M. Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS). From Agents to Copilots: A Systematic Review of Digital Assistant Technology Adoption in Proprietary Productivity Software View