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

AI Language Models in Health Care (224) Natural Language Processing (937) e-Learning and Digital Medical Education (932) Machine Learning (2173) Testing and Assessment in Medical Education (105) mHealth in Medical Education and Training (128) Theme Issue: ChatGPT and Generative Language Models in Medical Education (115)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69485, first published .
Performance of Large Language Models in the Non-English Context: Qualitative Study of Models Trained on Different Languages in Chinese Medical Examinations

Performance of Large Language Models in the Non-English Context: Qualitative Study of Models Trained on Different Languages in Chinese Medical Examinations

Performance of Large Language Models in the Non-English Context: Qualitative Study of Models Trained on Different Languages in Chinese Medical Examinations

Authors of this article:

Zhong Yao1, 2, 3 Author Orcid Image ;   Liantan Duan4 Author Orcid Image ;   Shuo Xu1, 2, 3 Author Orcid Image ;   Lingyi Chi1, 2, 3 Author Orcid Image ;   Dongfang Sheng4 Author Orcid Image
Article Authors Cited by (6) Tweetations Metrics

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  2. Meretukov D, Grechukhina K, Evdokimov V, Didych D, Kondratieva S, Rakitina O, Gordeev A, Shilo P, Khatkov I, Zhukova L. Deriving Real-World Evidence from Non-English Electronic Medical Records in Hormone Receptor-Positive Breast Cancer Using Large Language Models. Cancers 2025;17(23):3836 View
  3. Kaleci A, Şahinbaş B, Ağadayı E, Çelikkaya S, Altun A, Kardan E. Performance of Large Language Models in Medical Exams: A Comparison Between ChatGPT and Medical Students. Tıp Eğitimi Dünyası 2025;24(74):135 View
  4. Zhou Y, Wang W, Wang P, Hu K. Diagnostic performance of large language models on the NEJM image challenge: a comparative study with human evaluators and the impact of prompt engineering. Frontiers in Medicine 2026;12 View
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