Machine learning and SHAP value interpretation for predicting cardiovascular disease risk in patients with diabetes using dietary antioxidants
XGBoost exhibited the highest predictive performance for cardiovascular disease risk in diabetic patients. SHAP analysis underscored the prominent contribution of dietary antioxidants, with Daidzein and Mg emerging as the most influential predictors.
Authors
- Sen Lin (ORCID: https://orcid.org/0000-0002-9384-8128)
- Qiuming Zeng (ORCID: https://orcid.org/0000-0002-2021-1484)
- Chaoguang Yan (ORCID: https://orcid.org/0000-0002-4298-9457)
- Xinyu Zhang (ORCID: https://orcid.org/0009-0008-0290-7374)
- Lisheng Peng (ORCID: https://orcid.org/0009-0003-5208-2757)
Institutions
- Guangzhou University of Chinese Medicine (CN)
- Weifang Chinese Medicine Hospital (CN)
- Shenzhen Pingle Orthopedic Hospital (CN)
Publication Details
- Journal
- Frontiers in Nutrition
- Published
- 2025-07-16
- DOI
- https://doi.org/10.3389/fnut.2025.1612369
- Citations
- 1
- Primary Topic
- Nutritional Studies and Diet
- Type
- article
- Field-Weighted Citation Impact
- 1.88