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

Foundations of AI (47) Artificial Intelligence (1371) Applications of AI (80)

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

Authors of this article:

Hisashi Kurasawa1, 2 Author Orcid Image ;   Kayo Waki2 Author Orcid Image ;   Tomohisa Seki2 Author Orcid Image ;   Akihiro Chiba1, 3 Author Orcid Image ;   Akinori Fujino1 Author Orcid Image ;   Katsuyoshi Hayashi1 Author Orcid Image ;   Eri Nakahara1, 2 Author Orcid Image ;   Tsuneyuki Haga1, 4 Author Orcid Image ;   Takashi Noguchi5 Author Orcid Image ;   Kazuhiko Ohe2 Author Orcid Image
Article Authors Cited by Tweetations Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.