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

AI Language Models in Health Care (205) Natural Language Processing (917) e-Learning and Digital Medical Education (905) Machine Learning (2079) Testing and Assessment in Medical Education (93) mHealth in Medical Education and Training (121) 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 (2) Tweetations Metrics

Journals

  1. Zhong D, Liang Y, Yan H, Chen X, Yang Q, Ma S, Su Y, Chen Y, Huang X, Wang M. A Comparative Study of Five Large Language Models’ Response for Liver Cancer Comprehensive Treatment. Journal of Hepatocellular Carcinoma 2025;Volume 12:1861 View
  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