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Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants

BACKGROUND: Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-optimal performance across all patient groups. Data-...

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Detalles Bibliográficos
Autores principales:	Alaa, Ahmed M., Bolton, Thomas, Di Angelantonio, Emanuele, Rudd, James H. F., van der Schaar, Mihaela
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2019
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6519796/ https://www.ncbi.nlm.nih.gov/pubmed/31091238 http://dx.doi.org/10.1371/journal.pone.0213653

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