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

Theme Issue: ChatGPT and Generative Language Models in Medical Education (86) Testing and Assessment in Medical Education (55) Artificial Intelligence (96) Chatbots and Conversational Agents (543) Generative Language Models Including ChatGPT (325)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55048, first published .
Exploring the Performance of ChatGPT Versions 3.5, 4, and 4 With Vision in the Chilean Medical Licensing Examination: Observational Study

Exploring the Performance of ChatGPT Versions 3.5, 4, and 4 With Vision in the Chilean Medical Licensing Examination: Observational Study

Exploring the Performance of ChatGPT Versions 3.5, 4, and 4 With Vision in the Chilean Medical Licensing Examination: Observational Study

Authors of this article:

Marcos Rojas1 Author Orcid Image ;   Marcelo Rojas2 Author Orcid Image ;   Valentina Burgess2 Author Orcid Image ;   Javier Toro-Pérez2 Author Orcid Image ;   Shima Salehi1 Author Orcid Image
Article Authors Cited by (5) Tweetations (5) Metrics

Journals

  1. Liu M, Okuhara T, Chang X, Shirabe R, Nishiie Y, Okada H, Kiuchi T. Performance of ChatGPT Across Different Versions in Medical Licensing Examinations Worldwide: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2024;26:e60807 View
  2. Tong W, Zhang X, Zeng H, Pan J, Gong C, Zhang H. Reforming China’s Secondary Vocational Medical Education: Adapting to the Challenges and Opportunities of the AI Era. JMIR Medical Education 2024;10:e48594 View
  3. Kipp M. From GPT-3.5 to GPT-4.o: A Leap in AI’s Medical Exam Performance. Information 2024;15(9):543 View
  4. LEVENTOGLU E, SORAN M. Clinical Characteristics of Children with Acute Post-Streptococcal Glomerulonephritis and Re-Evaluation of Patients with Artificial Intelligence. Medeniyet Medical Journal 2024 View
  5. Nakaura T, Yoshida N, Kobayashi N, Nagayama Y, Uetani H, Kidoh M, Oda S, Funama Y, Hirai T. Performance of Multimodal Large Language Models in Japanese Diagnostic Radiology Board Examinations (2021-2023). Academic Radiology 2024 View