Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56700, first published .
Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development

Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development

Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development

Hisashi Kurasawa   1, 2 * , PhD ;   Kayo Waki   2 * , MPH, MD, PhD ;   Tomohisa Seki   2 , MD, PhD ;   Akihiro Chiba   1, 3 , PhD ;   Akinori Fujino   1 , PhD ;   Katsuyoshi Hayashi   1 , PhD ;   Eri Nakahara   1, 2 , ME ;   Tsuneyuki Haga   1, 4 , PhD ;   Takashi Noguchi   5 , MD, PhD ;   Kazuhiko Ohe   2 , MD, PhD

1 Nippon Telegraph and Telephone Corporation, Tokyo, Japan

2 The University of Tokyo Hospital, Tokyo, Japan

3 NTT DOCOMO, Inc, Tokyo, Japan

4 NTT-AT IPS Corporation, Kanagawa, Japan

5 National Center for Child Health and Development, Tokyo, Japan

*these authors contributed equally

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