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

Artificial Intelligence (AI) in Medical Education (626) e-Learning and Digital Medical Education (1511) eHealth Literacy / Digital Literacy (847) Testing and Assessment in Medical Education (194) Chatbots and Conversational Agents (1115) Artificial Intelligence (4447) Generative Language Models Including ChatGPT (1371)

Published on in Vol 12 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/81399, first published .
Medical students in a modern classroom using laptops and studying

Performance Evaluation of Large Language Models in Multilingual Medical Multiple-Choice Questions: Mixed Methods Study

Performance Evaluation of Large Language Models in Multilingual Medical Multiple-Choice Questions: Mixed Methods Study

Authors of this article:

Livia Maria Strasser1 Author Orcid Image ;   Wilma Anschuetz2 Author Orcid Image ;   Fabio Dennstädt1, 3 Author Orcid Image ;   Janna Hastings1, 4, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Kondo T, Donkers J, Nishigori H, Rovers S, Heeneman S. AI-Generated Versus Human Supervisor Feedback on Medical Students’ Clinical Clerkship Logs: Cross-Sectional Convergent Mixed Methods Study. JMIR Medical Education 2026;12:e90064 View
  2. Siebielec J, Raciborski F. Assessment of vaccine information accuracy across large language models. Frontiers in Public Health 2026;14 View