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

Weiping Wang   1 * , PhD ;   Yuchen Zhou   1, 2 * , MD ;   Jingxuan Fu   3 * , PhD ;   Ke Hu   1 , PhD

1 Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

2 Tsinghua Medicine, School of Medicine, Tsinghua University, Beijing, China

3 Department of clinical laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China

*these authors contributed equally

Corresponding Author:

  • Ke Hu, PhD
  • Department of Radiation Oncology
  • Peking Union Medical College Hospital
  • Chinese Academy of Medical Sciences & Peking Union Medical College
  • Shuaifuyuan No. 1
  • Dongcheng District
  • Beijing 100730
  • China
  • Phone: 86 13701011034
  • Email: huke8000@126.com