Improving predictive performance in incident heart failure using machine learning and multi-center data

Improving predictive performance in incident heart failure using machine learning and multi-center data

ObjectiveTo mitigate the burden associated with heart failure (HF), primary prevention is of the utmost importance. To improve early risk stratification, advanced computational methods such as machine learning (ML) capturing complex individual patterns in large data might be necessary. Therefore, we...

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Bibliographic Details
Main Authors: František Sabovčik, Evangelos Ntalianis, Nicholas Cauwenberghs, Tatiana Kuznetsova
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
heart failure
incidence
machine learning
prediction model
multi-center data
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2022.1011071/full

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https://www.frontiersin.org/articles/10.3389/fcvm.2022.1011071/full

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