Development and validation of a machine learning predictive model for one-month post-revascularization angina in patients who had undergone PCI or CABG
This RF model offers a robust, interpretable tool for early PRA risk stratification, integrating cardiac, hemostatic, psychological, and metabolic factors. It supports personalized post-revascularization care, though prospective, multi-ethnic validation is needed to enhance generalizability.
Authors
- Conghui Zhou (ORCID: https://orcid.org/0000-0003-1698-1846)
- Yi-Xiang Wang (ORCID: https://orcid.org/0000-0002-4021-4228)
- Jingqing Hu
- Bihua Tang
Institutions
- Tianjin University of Traditional Chinese Medicine (CN)
- Nanjing University of Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2026-02-13
- DOI
- https://doi.org/10.3389/fcvm.2026.1747832
- Primary Topic
- Cardiac Health and Mental Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Key Research and Development Program of China