Mortality prediction of inpatients with NSTEMI in a premier hospital in China based on stacking model.

Journal: PloS one

PMID: 39739714

Abstract

BACKGROUND: Acute myocardial infarction (AMI) remains a leading cause of hospitalization and death in China. Accurate mortality prediction of inpatient is crucial for clinical decision-making of non-ST-segment elevation myocardial infarction (NSTEMI) patients.

Authors

Li Wang

College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
Yu Zhang

College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
Feng Li

Department of General Surgery, Shanghai Traditional Chinese Medicine (TCM)-INTEGRATED Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Caiyun Li

Department of Cardiology, The People's Hospital of China Medical University, The People's Hospital of Liaoning Province, Shenyang, China.
Hongzeng Xu

Department of Cardiology, The People's Hospital of China Medical University, The People's Hospital of Liaoning Province, Shenyang, China.

Keywords

Aged Algorithms China Decision Trees Female Hospital Mortality Hospitalization Humans Inpatients Logistic Models Male Middle Aged Non-ST Elevated Myocardial Infarction Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (39739714)

Mortality prediction of inpatients with NSTEMI in a premier hospital in China based on stacking model.

Abstract

Authors

Keywords

External Resources

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