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

Machine Learning (3373) Clinical Informatics (2421) Clinical Information and Decision Making (3942) Decision Support for Health Professionals (2386) ePrescribing and Innovations in Pharmacies (113) Artificial Intelligence (5085) Artificial Intelligence in Diabetes Care and Prevention (117)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67748, first published .
Man holding a white prescription pill bottle in a pharmacy

Enhancing Antidiabetic Drug Selection Using Transformers: Machine-Learning Model Development

Enhancing Antidiabetic Drug Selection Using Transformers: Machine-Learning Model Development

Authors of this article:

Hisashi Kurasawa1, 2 Author Orcid Image ;   Kayo Waki1 Author Orcid Image ;   Tomohisa Seki1 Author Orcid Image ;   Eri Nakahara1, 2 Author Orcid Image ;   Akinori Fujino2 Author Orcid Image ;   Nagisa Shiomi2 Author Orcid Image ;   Hiroshi Nakashima2 Author Orcid Image ;   Kazuhiko Ohe1 Author Orcid Image
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Journals

  1. Lozhkina A, Piazza C, Gabr Z, Rupp M, Herzig D, Bally L, Jaun A. Individualized Therapy Optimization for Type 2 Diabetes: Retrospective Study of Model Development, Internal Validation, and Physician Evaluation. JMIR Formative Research 2026;10:e92877 View