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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...
| Autores principales: | , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2021
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| Materias: | |
| 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 |