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

OBJECTIVE: To 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,...

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Detalles Bibliográficos
Autores principales: Sabovčik, František, Ntalianis, Evangelos, Cauwenberghs, Nicholas, Kuznetsova, Tatiana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Cardiovascular Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9623026/
https://www.ncbi.nlm.nih.gov/pubmed/36330000
http://dx.doi.org/10.3389/fcvm.2022.1011071

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9623026/
https://www.ncbi.nlm.nih.gov/pubmed/36330000
http://dx.doi.org/10.3389/fcvm.2022.1011071

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