Predicting Major Adverse Cardiovascular Events After Cardiac Surgery Using Combined Clinical, Laboratory, and Echocardiographic Parameters: A Machine Learning Approach

<i>Background and Objectives:</i> Despite significant advances in surgical techniques and perioperative care, major adverse cardiovascular events (MACE) remain a leading cause of postoperative morbidity and mortality in patients undergoing coronary artery bypass grafting and/or aortic valve replacem...

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Bibliografiska uppgifter

Huvudupphov:	Mladjan Golubovic, Velimir Peric, Marija Stosic, Vladimir Stojiljkovic, Sasa Zivic, Aleksandar Kamenov, Dragan Milic, Vesna Dinic, Dalibor Stojanovic, Milan Lazarevic
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2025-07-01
Serie:	Medicina
Ämnen:	major adverse cardiovascular events coronary artery bypass aortic valve replacement predictive modeling machine learning
Länkar:	https://www.mdpi.com/1648-9144/61/8/1323
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