Prediction of cardiovascular risk using machine-learning methods. Sex-specific differences

Prediction of cardiovascular risk using machine-learning methods. Sex-specific differences

BackgroundMachine learning (ML) algorithms offer some advantages over traditional scoring systems to assess the influence of cardiovascular risk factors (CVRFs) on the risk of major cardiovascular event (MACE), and could be useful in clinical practice. These algorithms can also be trained using a gr...

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Bibliographic Details
Main Authors: Sara Castel-Feced, Isabel Aguilar-Palacio, Sara Malo, Juan González-García, Lina Maldonado, María José Rabanaque-Hernández
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
machine learning
cardiovascular disease
adherence to treatment
random forest
XGBoost
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2025.1579947/full
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https://www.frontiersin.org/articles/10.3389/fcvm.2025.1579947/full

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