Prediction of Insulin Requirements by Explainable Machine Learning for Individuals With Type 1 Diabetes
We here developed machine-learning models that predict the TDD of insulin from clinical information. Such models could contribute to the treatment of many individuals undergoing insulin therapy, with further developments being warranted.
Authors
- Shin Urai (ORCID: https://orcid.org/0000-0002-7996-232X)
- Seiji Nishikage (ORCID: https://orcid.org/0009-0007-4348-6118)
- Yushi Hirota (ORCID: https://orcid.org/0000-0002-3035-4155)
- Wataru Ogawa (ORCID: https://orcid.org/0000-0002-0432-4366)
- Kai Yoshimura (ORCID: https://orcid.org/0009-0002-6144-1320)
- Tomofumi Takayoshi
- Shuichiro Saito
- Akane Yamamoto
Institutions
- Kobe University (JP)
Publication Details
- Journal
- The Journal of Clinical Endocrinology & Metabolism
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1210/clinem/dgae863
- Citations
- 2
- Primary Topic
- Diabetes Management and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.72