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

Theme Issue: ChatGPT and Generative Language Models in Medical Education (66) Chatbots and Conversational Agents (458) e-Learning and Medical Education (645) Artificial Intelligence (1186) Natural Language Processing (636) New Methods and Approaches in Medical Education (192) Testing and Assessment in Medical Education (38)

Published on in Vol 9 (2023)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50514, first published .
Assessment of Resident and AI Chatbot Performance on the University of Toronto Family Medicine Residency Progress Test: Comparative Study

Assessment of Resident and AI Chatbot Performance on the University of Toronto Family Medicine Residency Progress Test: Comparative Study

Assessment of Resident and AI Chatbot Performance on the University of Toronto Family Medicine Residency Progress Test: Comparative Study

Authors of this article:

Ryan ST Huang1 Author Orcid Image ;   Kevin Jia Qi Lu2 Author Orcid Image ;   Christopher Meaney2 Author Orcid Image ;   Joel Kemppainen2 Author Orcid Image ;   Angela Punnett1, 3 Author Orcid Image ;   Fok-Han Leung2 Author Orcid Image
Article Authors Cited by (8) Tweetations (4) Metrics

Journals

  1. Komasawa N, Yokohira M. Learner-Centered Experience-Based Medical Education in an AI-Driven Society: A Literature Review. Cureus 2023 View
  2. Tangadulrat P, Sono S, Tangtrakulwanich B. Using ChatGPT for Clinical Practice and Medical Education: Cross-Sectional Survey of Medical Students’ and Physicians’ Perceptions. JMIR Medical Education 2023;9:e50658 View
  3. Sallam M, Barakat M, Sallam M. A Preliminary Checklist (METRICS) to Standardize the Design and Reporting of Studies on Generative Artificial Intelligence–Based Models in Health Care Education and Practice: Development Study Involving a Literature Review. Interactive Journal of Medical Research 2024;13:e54704 View
  4. Arslan B, Eyupoglu G, Korkut S, Turkdogan K, Altinbilek E. The accuracy of AI-assisted chatbots on the annual assessment test for emergency medicine residents. Journal of Medicine, Surgery, and Public Health 2024;3:100070 View
  5. Günay S, Öztürk A, Özerol H, Yiğit Y, Erenler A. Comparison of emergency medicine specialist, cardiologist, and chat-GPT in electrocardiography assessment. The American Journal of Emergency Medicine 2024;80:51 View
  6. Katz U, Cohen E, Shachar E, Somer J, Fink A, Morse E, Shreiber B, Wolf I. GPT versus Resident Physicians — A Benchmark Based on Official Board Scores. NEJM AI 2024;1(5) View
  7. Komasawa N. Transformative Landscape of Anesthesia Education: Simulation, AI Integration, and Learner-Centric Reforms: A Narrative Review. Anesthesia Research 2024;1(1):34 View
  8. Mousavi M, Shafiee S, Harley J, Cheung J, Abbasgholizadeh Rahimi S. Performance of generative pre-trained transformers (GPTs) in Certification Examination of the College of Family Physicians of Canada. Family Medicine and Community Health 2024;12(Suppl 1):e002626 View