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

Abstract 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 nationa...

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Bibliographic Details
Main Authors: Soongu Kwak, Hyun-Jung Lee, Seungyeon Kim, Jun-Bean Park, Seung-Pyo Lee, Hyung-Kwan Kim, Yong-Jin Kim
Format: Article
Language:English
Published: Nature Portfolio 2023-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-36450-4