Machine learning reveals sex-specific associations between cardiovascular risk factors and incident atherosclerotic cardiovascular disease

We aimed to investigate sex-specific associations between cardiovascular risk factors and atherosclerotic cardiovascular disease (ASCVD) risk using machine learning. We studied 258,279 individuals (132,505 [51.3%] men and 125,774 [48.7%] women) without documented ASCVD who underwent national health...

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Detalles Bibliográficos
Autores principales: Kwak, Soongu, Lee, Hyun-Jung, Kim, Seungyeon, Park, Jun-Bean, Lee, Seung-Pyo, Kim, Hyung-Kwan, Kim, Yong-Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250402/
https://www.ncbi.nlm.nih.gov/pubmed/37291421
http://dx.doi.org/10.1038/s41598-023-36450-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250402/
https://www.ncbi.nlm.nih.gov/pubmed/37291421
http://dx.doi.org/10.1038/s41598-023-36450-4

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