Machine Learning‐Driven Prediction of Coronary Artery Disease Risk Based on UK Biobank Plasma Proteomics

Background Coronary artery disease (CAD) is a leading global cause of mortality, yet the predictive accuracy of conventional risk models is limited. Here, we integrate conventional risk factors, polygenic risk scores, and large‐scale proteomics to develop a unified model for enhanced CAD risk predic...

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Hlavní autoři:	Yuezhong Huang, Xiaoli Chen, Hao Zhang, Zhanpei Bai, Yifan Shen, Daishan Zheng, Longyu Fang, Hongzi Song, Hebei Gao, Fan Lu, Xiu‐Feng Huang
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Wiley 2026-06-01
Edice:	Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Témata:	coronary artery disease machine learning polygenic risk score proteomics risk prediction
On-line přístup:	https://www.ahajournals.org/doi/10.1161/JAHA.125.047248
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