Accessibility settings

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79039, first published .
Woman in telehealth appointment with doctor, looking distressed

Large Language Model–Based Virtual Patient Systems for History-Taking in Medical Education: Comprehensive Systematic Review

Large Language Model–Based Virtual Patient Systems for History-Taking in Medical Education: Comprehensive Systematic Review

Authors of this article:

Dongliang Li1 Author Orcid Image ;   Syaheerah Lebai Lutfi2 Author Orcid Image

Journals

  1. Li S, Wang X, Chen Y, Tian M, Lin P, Lai M, Jiang L. Large language models for primary care ophthalmic education: a systematic review. Frontiers in Medicine 2026;13 View
  2. Glinkowski W, Jacennik B, Jankowska A, Cedro T, Wilk S, Doniec R. AI-Assisted Training for Teleconsultation Competencies in Undergraduate Medical Education: A Narrative Review. Applied Sciences 2026;16(10):4858 View
  3. Qu Y, Xu X, Long Y, Wang Y, Li J, Lu X. A Large Language Model–Powered Multiagent Framework Emulating Standardized Patients in Clinical Communication Skills Training: Development and Evaluation Study. Journal of Medical Internet Research 2026;28:e84747 View
  4. Zhang Y, Zhou H, Huo H, Yue Y, Wang J, Zhu J. AI-based virtual patient training for clinical communication skills in dental undergraduates: A randomized controlled mixed methods study. Medical Teacher 2026:1 View
  5. Haut K, Hasan M, Carroll T, Epstein R, Sen T, Hoque E. The Effects of Generative AI Virtual Patient in Serious Illness Communication Skills: Randomized Controlled Trial (Preprint). JMIR Medical Education 2026 View
  6. Sindhvananda K, Ruengwattanachot K, Leksuwankun S, Pongpitakmetha T, Hiransuthikul A, Surawattanawong T, Anukoolwittaya P, Panjasriprakarn P. AI-powered simulated patients with automated feedback for enhancing headache history-taking skills: a convergent mixed-methods study. BMC Medical Education 2026;26(1) View
  7. Choi I, Kim J, Kim J, Lee H, Park W, Kim C, Lim D. A Curriculum-Embedded Two-Session AI Chatbot-Based History-Taking Practicum in Korean Medicine Diagnostics. Applied Sciences 2026;16(14):7223 View
  8. Ye Y, Tao H, Huang S, Zou M, Chen Y, Shen P, Hao M, Liu C. Virtual patients in medical education: a bibliometric analysis based on the wos core collection and scopus databases. Frontiers in Medicine 2026;13 View
  9. K S, K L A, Kerala Varma P, B P, K P A, Agnihotri V, Muthu P, Bhaskaran R, Nair N. Nurse-Led Large Language Model Chatbot for Predicting and Preventing Complications After Coronary Artery Bypass Grafting: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2026;15:e103717 View
  10. Fan T, Gao T, Tang W, Xu Q, Wang X, Su Q, Lyu Q. Large language models in emergency medicine education: opportunities, challenges, and implementation pathways. Frontiers in Public Health 2026;14 View
  11. Alefragkis D, Aloizou D, Chougia V. A Large Language Model-Based Simulation Protocol Using ChatGPT for Training Novice Critical Care Nurses in Family Crisis Communication and De-escalation. Cureus 2026 View
  12. Zhang W, Daniels B, Mita C, Nguyen H, Duong D. AI for Clinical Competency Assessment: Scoping Review of Methods and Applications. JMIR Medical Education 2026;12:e92826 View

Books/Policy Documents

  1. Fouad S, Muskwe L, Harib W, Hassan-Smith G. Artificial Intelligence in Healthcare. View

Conference Proceedings

  1. Gao Z, Zhu G, Luo H, Primo Pan D, Tang H, Zhang B, Pei J, Li J, Wang B. Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems. "It Talks Like a Patient, But Feels Different": Co-Designing AI Standardized Patients with Medical Learners View
  2. Rick S, Bedmutha M, Arriaga R, De Choudhury M, Goldberg C, Ismail A, Kumar N, Kwon H, Pratt W, Singh A, Wong A, Xu X, Weibel N. Proceedings of the 2026 ACM Interactive Health Conference. GenAI and Synthetic Data in Healthcare: Exploring the Design and Use of AI-Generated Data for Interactive Health Systems View