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Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77552, first published .
Four young Asian students collaborate on a laptop, analyzing data with a magnifying glass.

Perceptions and Intentions to Use Generative AI Among First-Year Medical Students in Japan: Cross-Sectional Survey Study

Perceptions and Intentions to Use Generative AI Among First-Year Medical Students in Japan: Cross-Sectional Survey Study

Journals

  1. Lu M, Cheng J, Gopalan V. Performance of multimodal large language models on image‐based surgical anatomy, anatomical pathology, and radiology questions. Anatomical Sciences Education 2026;19(8):1288 View
  2. Jakob F, Glueer C, Thomasius F. Ein neuer Dreiklang: Von der Eminenz zur Evidenz zur Künstlichen Intelligenz. Osteologie 2026;35(02):121 View
  3. Paris F, Garrouste V, Abensur Vuillaume L. Perceptions, Attitudes, and Use of AI by Medical Students: Mixed Methods Study. JMIR Medical Education 2026;12:e91345 View
  4. Zhang W, Han J, Han X, Xu H, Wang L, Lin T, Tan P, Zhang P, Zheng X. Medical Students’ Attitudes, Perceptions, and Self-Reported Familiarity With AI in Health Care: Systematic Review and Meta-Analysis. JMIR Medical Education 2026;12:e89411 View

Conference Proceedings

  1. Xu S, Xu X. Proceedings of the 2026 International Conference on Artificial Intelligence in Education Technology and Data Science. A Trustworthiness Assurance Framework for Generative Educational Content to Enhance Teaching Effectiveness View