Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk factors

Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk factors

Abstract Background Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally. Traditional risk models, primarily based on established risk factors, often lack the precision needed to accurately predict new-onset major adverse cardiovascular events (MACE). This study...

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Main Authors: Xi-Ru Zhang, Wen-Fang Zhong, Rui-Yan Liu, Jie-Lin Huang, Jing-Xiang Fu, Jian Gao, Pei-Dong Zhang, Dan Liu, Zhi-Hao Li, Yan He, Hongwei Zhou, Zhuang Li
Format: Article
Language:English
Published: BMC 2025-04-01
Series:Cardiovascular Diabetology
Subjects:
Cardiovascular research
Major adverse cardiovascular events
Biomarker risk score
Risk stratification
Binary threshold
Online Access:https://doi.org/10.1186/s12933-025-02711-x
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https://doi.org/10.1186/s12933-025-02711-x

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