Cardiovascular risk assessment enhanced by automated machine learning in a multi-phase study

Abstract Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and current predictors such as lipoprotein (a) [Lp(a)] and risk scores have limitations. Automated machine learning (AutoML) offers the potential to improve CVD risk prediction by processing large datasets and developi...

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מידע ביבליוגרפי

Principais autores:	Igor Bibi, Daniel Schaffert, Philipp Blanke, Lorenz Illian, Federico Lenzing, Niklas Martin, Jan Leipe, Winfried März, Ksenija Stach, Victor Olsavszky
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Nature Portfolio 2025-10-01
סדרה:	Scientific Reports
נושאים:	Automated machine learning Cardiovascular diseases Predictive modeling Risk stratification Clinical datasets
גישה מקוונת:	https://doi.org/10.1038/s41598-025-24189-z
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