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Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73419, first published .
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

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

Journals

  1. Bartkowski J, Zerdka J, Brasse P, Piszka M, Kwapien E, Staszkiewicz K, Kubicka M, Staszkiewicz K, Czarnecki F. Artificial Intelligence in Medicine With Emphasis on Orthopedic Practice. Cureus 2025 View
  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