Predicting the rapid progression of coronary artery lesions in patients with acute coronary syndrome based on machine learning
The RF model exhibits high accuracy and generalizability in predicting RCAL, thereby providing a valuable instrument to assist clinical decision-making.
Authors
- Hua Ouyang
- Jun Yang (ORCID: https://orcid.org/0000-0003-1652-0054)
- Songran Yang (ORCID: https://orcid.org/0000-0002-2490-7091)
- Huanwei Zhuang
- Long Gui (ORCID: https://orcid.org/0000-0002-2629-0689)
- Heshan Cao (ORCID: https://orcid.org/0009-0006-0594-4141)
- Ping Hua
- Yubo Hu (ORCID: https://orcid.org/0000-0003-2049-3829)
- Yangfei Peng
Institutions
- Central South University (CN)
- Sun Yat-sen University (CN)
- Hainan University (CN)
- Sun Yat-sen Memorial Hospital (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2025-09-05
- DOI
- https://doi.org/10.3389/fcvm.2025.1535406
- Primary Topic
- Coronary Interventions and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China