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

New Resources for Medical Education (118) Generative Language Models Including ChatGPT (734) Artificial Intelligence (AI) in Medical Education (196) Testing and Assessment in Medical Education (101)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73469, first published .
Evaluating the Performance of DeepSeek-R1 and DeepSeek-V3 Versus OpenAI Models in the Chinese National Medical Licensing Examination: Cross-Sectional Comparative Study

Evaluating the Performance of DeepSeek-R1 and DeepSeek-V3 Versus OpenAI Models in the Chinese National Medical Licensing Examination: Cross-Sectional Comparative Study

Evaluating the Performance of DeepSeek-R1 and DeepSeek-V3 Versus OpenAI Models in the Chinese National Medical Licensing Examination: Cross-Sectional Comparative Study

Authors of this article:

Weiping Wang1 Author Orcid Image ;   Yuchen Zhou1, 2 Author Orcid Image ;   Jingxuan Fu3 Author Orcid Image ;   Ke Hu1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Stoyanov A, Nedelcheva A. Identifying Features of LLM-Resistant Exam Questions: Insights from Artificial Intelligence (AI)–Student Performance Comparisons. Sci 2025;7(4):183 View
  2. Sudo H, Noborimoto Y, Takahashi J. Evaluation of Few-Shot AI-Generated Feedback on Case Reports in Physical Therapy Education: Mixed Methods Study. JMIR Medical Education 2025;11:e85614 View