Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study
The fine-tuned GLM4-9B shows strong potential as a clinical decision support tool for personalized diabetes care. It can provide reference recommendations that may improve clinician efficiency and support decision quality. Future work should focus on enhancing medication guidance, expanding data sources, and improving adaptability in cases involving complex comorbidities.
Authors
- shenyang he
- Jiaxi Li
- Yu Zhang
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Maternal and Child Health Hospital of Sichuan Province (CN)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2026-02-09
- DOI
- https://doi.org/10.2196/71541
- Citations
- 1
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 52.10