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

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
  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