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Published on in Vol 11 (2025)

This is a member publication of University of Bath (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70766, first published .
Doctor consults with elderly patient via telehealth video call on computer.

Application of AI Communication Training Tools in Medical Undergraduate Education: Mixed Methods Feasibility Study Within a Primary Care Context

Application of AI Communication Training Tools in Medical Undergraduate Education: Mixed Methods Feasibility Study Within a Primary Care Context

Journals

  1. L.C P, Suryavanshi C, Prabhu K, Chauhan A, Raghurama Nayak K, Komattil R, Baig M. Enhancing medical communication skills through video-recorded peer role-play and a standardized checklist. PLOS One 2026;21(2):e0343202 View
  2. Sun N, Zhou X, Yang Z, Zhou Y, Ma R, Wang Z. Application of AI-based virtual standardized patients in physician-patient communication training: a study based on the SEGUE framework. Frontiers in Public Health 2026;14 View
  3. 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
  4. Jacobs C, Johnson H, Joiner R, Thompson T. A Letter about “AI-Standardized Clinical Examination Training on OSCE Performance”. NEJM AI 2026;3(6) View
  5. Yauy K, Lavigne E, Gabellier L, Pers Y, Lopez A. The Targeted Educational Role of Text-Based AI-Standardized Clinical Examination. NEJM AI 2026;3(6) View
  6. Thind B, Javidi D, Schwartz L. Artificial intelligence in undergraduate medical education clinical skills curricula: a scoping review of implementations since 2022. Frontiers in Digital Health 2026;8 View
  7. Lima G, Morton S. Caring in the Age of AI: A Framework for the Pediatric Trainee. Pediatrics 2026;158(1) View
  8. Losada J, Sarriugarte A, Losada I. Modelo integrado de decisión clínica, bayesiana, ética y de aprendizaje por refuerzo para la estrategia de observar y esperar frente a la cirugía en cáncer de recto. Educación Médica 2026;27(4):101205 View
  9. Jeong I, Kim H, Hwang H. Generative artificial intelligence and large language models in competency-based medical education: applications, challenges, and future directions. Kosin Medical Journal 2026;41(2):114 View
  10. Herschbach L, Festl-Wietek T, Sonanini A, Holderried F, Albrecht T, Herrmann B, Herrmann-Werner A. AI-Simulated Patients for Training Shared Decision-Making: Feasibility Study in Medical Education. JMIR Medical Education 2026;12:e100467 View
  11. Jia C, Qi L. Digital Standardized Patients: Conceptual Framework for Generative AI–Empowered Medical Education. JMIR Medical Education 2026;12:e91050 View
  12. Ismail N, Zafira A. Artificial intelligence for affective-domain development in healthcare professions education: a systematic review. Frontiers in Medicine 2026;13 View
  13. Cohen H, Smith B, Day N, Jacobs C, Reid D. AI patients, real practice: exploring the use of AI-simulated patients to support primary healthcare training for combat medical technicians. Education for Primary Care 2026:1 View
  14. Paget E. Identifying implementation considerations for the use of AI-VR simulation in undergraduate healthcare: A pilot feasibility study. DIGITAL HEALTH 2026;12 View
  15. Kaplan K, Pravdo A, Reoli R. Doctor of physical therapy students’ perceptions of artificial intelligence chatbots versus peer role play for therapeutic interviewing practice. Physiotherapy Theory and Practice 2026:1 View