Multi-feature integrated machine learning prediction model for early nephropathy in elderly living with type 2 diabetes mellitus
This study is the first to incorporate TCM symptoms and ultrasound imaging features into a predictive model for early DN in elderly living with T2DM. The models demonstrated strong predictive performance across different age groups. These findings underscore the potential of early screening, prevention, and intervention in improving outcomes for elderly living with T2DM, offering a novel approach to managing diabetic nephropathy.
Authors
- Tingting Fang (ORCID: https://orcid.org/0009-0003-9942-8794)
- Linghua Kong (ORCID: https://orcid.org/0000-0001-8289-4180)
- Xinran Xie
- Yuanyuan Yang
- Jialun Song
- Feng Zhuo
Institutions
- Shandong University (CN)
- Shandong Provincial Hospital (CN)
- Dalian Maritime University (CN)
Publication Details
- Journal
- Frontiers in Endocrinology
- Published
- 2026-01-21
- DOI
- https://doi.org/10.3389/fendo.2025.1660903
- Primary Topic
- Chronic Kidney Disease and Diabetes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Hangzhou Normal University
- Young Scientists Fund