Enhancing one-year mortality prediction in STEMI patients post-PCI: an interpretable machine learning model with risk stratification
This study highlights the feasibility of constructing accurate and interpretable ML models using a minimal set of predictors, supplemented by risk stratification, to improve long-term outcome prediction in STEMI patients.
Authors
- Xiaoyan Su (ORCID: https://orcid.org/0000-0001-6132-6969)
- Wei Hu (ORCID: https://orcid.org/0000-0001-9629-2121)
- Wenqiang Li (ORCID: https://orcid.org/0000-0002-0833-246X)
- Zheng Zhang (ORCID: https://orcid.org/0000-0002-0027-172X)
- Dongdong Yan (ORCID: https://orcid.org/0000-0002-9448-6464)
Institutions
- Qinghai Provincial Peoples Hospital (CN)
- First Hospital of Lanzhou University (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2025-08-22
- DOI
- https://doi.org/10.3389/frai.2025.1618492
- Citations
- 1
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Key Research and Development Program of China