Machine learning algorithms mimicking specialists decision making on initial treatment for people with type 2 diabetes mellitus in Japan diabetes data management study (JDDM76).

Journal: Diabetes & metabolic syndrome
PMID: 39644730

Abstract

OBJECTIVE: To evaluate whether typical machine learning models that mimic specialists' care can successfully reproduce information, not only on whether to prescribe medications but also which hypoglycemic agents to prescribe as initial treatment for type 2 diabetes.

Authors

  • Jenny Elizabeth Price
    Graduate School of Science and Technology, Niigata University, Niigata, Japan.
  • Kazuya Fujihara
    Department of Hematology, Endocrinology and Metabolism, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
  • Satoru Kodama
    Department of Hematology, Endocrinology and Metabolism, University Faculty of Medicine, Niigata, Japan.
  • Katsuya Yamazaki
    Kawai Clinic, Tsukuba, Japan.
  • Hiroshi Maegawa
    Department of Medicine, Shiga University of Medical Science, Shiga, Japan.
  • Tatsuya Yamazaki
    Faculty of Engineering, Niigata University, Niigata, Japan.
  • Hirohito Sone
    Faculty of Medicine, Department of Hematology, Endocrinology and Metabolism, Niigata University, Niigata, Japan.

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