Interpretable machine learning model for cardiovascular disease risk prediction: a feature decomposition-based study
We have developed an ML model for predicting the risk of CVDs. This model shows potential to assist clinicians in identifying high-risk patients and providing a theoretical basis for personalized preventive healthcare measures.
Authors
- Xin Wu
- Daikun Zheng (ORCID: https://orcid.org/0000-0002-6414-2548)
- Chenxi Chen (ORCID: https://orcid.org/0000-0002-7094-3296)
- Fang Li (ORCID: https://orcid.org/0000-0003-1477-3875)
- Liliang Yu
- Yuanjun Chen (ORCID: https://orcid.org/0000-0003-4465-3583)
- Jian-Cheng Wu
Institutions
- Hebei Meteorological Bureau (CN)
- Chongqing Emergency Medical Center (CN)
- Chongqing Three Gorges University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-10-28
- DOI
- https://doi.org/10.1186/s12889-025-24921-4
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 8.81
Funders
- Centre Scientifique et Technique du Bâtiment