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This paper is in the following e-collection/theme issue:

Virtual Patients (91) e-Learning and Digital Medical Education (1008) Preliminary Experiences with New Educational Technology (53) New Methods and Approaches in Medical Education (450) mHealth in Medical Education and Training (143) Machine Learning (2323) Development and Evaluation of Research Methods, Instruments and Tools (858) Theme Issue: ChatGPT and Generative Language Models in Medical Education (115) Ambient AI Scribes and AI-Driven Documentation Technologies (39)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73419, first published .
Medical team in a conference room with digital displays showing human anatomy

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

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

Authors of this article:

Yang Liu1 Author Orcid Image ;   Chujun Shi1 Author Orcid Image ;   Liping Wu1 Author Orcid Image ;   Xiule Lin1 Author Orcid Image ;   Xiaoqin Chen1 Author Orcid Image ;   Yiying Zhu1 Author Orcid Image ;   Haizhu Tan2 Author Orcid Image ;   Weishan Zhang1 Author Orcid Image
Article Authors Cited by (7) Tweetations Metrics

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  2. Zouakia Z, Logak E, Szymczak A, Jais J, Burgun A, Tsopra R. AI-Driven Objective Structured Clinical Examination Generation in Digital Health Education: Comparative Analysis of Three GPT-4o Configurations. JMIR Medical Education 2026;12:e82116 View
  3. Liu Y, Zhu Y, Zhang W, Lu X, Wu L, Yue M, Xia O, Shi C. Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study. JMIR Medical Education 2026;12:e89367 View
  4. Madwe M. Generative Artificial Intelligence Student Feedback in Large University Accounting Classes: Prompting Techniques. International Journal of Sustainability in Business and Economics 2026;2(1) View
  5. Vaira L, Qadeer H, Lechien J, Maniaci A, Maglitto F, Troise S, Chiesa-Estomba C, Consorti G, Cirignaco G, Iannella G, Navarro-Cuéllar C, Salzano G, Soro G, Boscolo-Rizzo P, Vellone V, De Riu G. Safety-First Framework for AI-Enabled Anamnesis in Head and Neck Surgery: Evidence Synthesis from a Narrative Review. Journal of Clinical Medicine 2026;15(6):2218 View
  6. Bonilla Mejia J, Cortés Fuenzalida T, Polanco Aliaga D, Martínez Carrillo C, Herrera Alcaíno Á. Inteligencia artificial en la formación clínica práctica de estudiantes de medicina de pregrado: una revisión de alcance de aplicaciones, resultados y brechas.. Revista Española de Educación Médica 2026;7(3) View
  7. BaHammam F. Feasibility of Large Language Model–Based Standardized Virtual Patients to Support Clinical Decision-Making Training in Operative Dentistry: Mixed Methods Study. JMIR Formative Research 2026;10:e91021 View