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

Journal: JMIR medical informatics
Published Date: Jun 2, 2025

Abstract

BACKGROUND: Diabetes affects millions worldwide. Primary care physicians provide a significant portion of care, and they often struggle with selecting appropriate medications.

Authors

  • Hisashi Kurasawa
    University of Tokyo, Tokyo, Japan Nippon Telegraph and Telephone Corporation, Tokyo, Japan.
  • Kayo Waki
    University of Tokyo, Tokyo, Japan kwaki-tky@umin.ac.jp.
  • Tomohisa Seki
    Department of Cardiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; Department of Emergency and Critical Care Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan.
  • Eri Nakahara
    NTT Basic Research Laboratories, Bio-Medical Informatics Research Center, Atsugi-shi, Japan.
  • Akinori Fujino
    Nippon Telegraph and Telephone Corporation, Tokyo, Japan.
  • Nagisa Shiomi
    NTT Basic Research Laboratories, Bio-Medical Informatics Research Center, Atsugi-shi, Japan.
  • Hiroshi Nakashima
    Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Kazuhiko Ohe
    Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Keywords

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