Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction

Current cardiovascular risk assessment tools use a small number of predictors. Here, we study how machine learning might: (1) enable principled selection from a large multimodal set of candidate variables and (2) improve prediction of incident coronary artery disease (CAD) events. An elastic net-bas...

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Detalles Bibliográficos
Autores principales: Agrawal, Saaket, Klarqvist, Marcus D.R., Emdin, Connor, Patel, Aniruddh P., Paranjpe, Manish D., Ellinor, Patrick T., Philippakis, Anthony, Ng, Kenney, Batra, Puneet, Khera, Amit V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672148/
https://www.ncbi.nlm.nih.gov/pubmed/34950898
http://dx.doi.org/10.1016/j.patter.2021.100364

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672148/
https://www.ncbi.nlm.nih.gov/pubmed/34950898
http://dx.doi.org/10.1016/j.patter.2021.100364

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