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

Artificial Intelligence (AI) in Medical Education (231) Generative Language Models Including ChatGPT (817) Theme Issue: ChatGPT and Generative Language Models in Medical Education (115) Pharmacology and Pharmaceutics (127) Chatbots and Conversational Agents (787)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76925, first published .
Performance Evaluation of 18 Generative AI Models (ChatGPT, Gemini, Claude, and Perplexity) in 2024 Japanese Pharmacist Licensing Examination: Comparative Study

Performance Evaluation of 18 Generative AI Models (ChatGPT, Gemini, Claude, and Perplexity) in 2024 Japanese Pharmacist Licensing Examination: Comparative Study

Performance Evaluation of 18 Generative AI Models (ChatGPT, Gemini, Claude, and Perplexity) in 2024 Japanese Pharmacist Licensing Examination: Comparative Study

Authors of this article:

Hiroyasu Sato1, 2 Author Orcid Image ;   Katsuhiko Ogasawara3, 4 Author Orcid Image ;   Hidehiko Sakurai2 Author Orcid Image
Article Authors Cited by (3) Tweetations (1) Metrics

Journals

  1. Tran T, Le U, Phan V. Evaluating the Accuracy and Educational Potential of Generative AI Models in Pharmacy Education: A Comparative Analysis of ChatGPT and Gemini Across Bloom’s Taxonomy. Pharmacy 2025;14(1):1 View
  2. Yoon Y, Baek W, Jo H, Hong C, Ji Y. The potential impact of generative AI across Miller’s pyramid of clinical competence: A systematic review. Nurse Education in Practice 2026;92:104775 View
  3. Kiyomiya K, Sato H, Omata A, Wakabayashi S, Ohno Y, Kawazoe H, Ohtani H. Current Use and Challenges of Generative Artificial Intelligence in Hospital Pharmacist Practice: A Cross-Sectional Questionnaire Survey. Iryo Yakugaku (Japanese Journal of Pharmaceutical Health Care and Sciences) 2026;52(3):136 View