Development and validation of predictive models for prognostic assessment in patients with acute non-ST-segment elevation myocardial infarction: a multicentre real-world study from China
The machine learning-based prognosis model significantly improves the performance of the current risk assessment model for predicting adverse clinical outcomes in NSTEMI patients.
Authors
- Chongyou Rao (ORCID: https://orcid.org/0000-0002-6405-0862)
- Wei Qin (ORCID: https://orcid.org/0000-0001-8042-8784)
- Hebin Che (ORCID: https://orcid.org/0009-0007-3060-0014)
- Zongren Li (ORCID: https://orcid.org/0000-0002-0246-7048)
- Wanling Wang
- Wei Liu
- Kunlun He
- Bo Liu
- Jixian Gao
- Liqiang Fu
- Qin Zhong
Institutions
- Yuncheng University (CN)
- Chinese PLA General Hospital (CN)
- Chengde Medical University (CN)
- People's Hospital of Cangzhou (CN)
- Xuzhou Central Hospital (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2026-02-16
- DOI
- https://doi.org/10.1186/s12911-026-03385-5
- Primary Topic
- Acute Myocardial Infarction Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00