Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study

Abstract Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as possible and move from a one-size-fits-all approach to a precision cardiometabolic prevention strategy in the general population. We used data f...

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Autores principales: Guy Fagherazzi, Lu Zhang, Gloria Aguayo, Jessica Pastore, Catherine Goetzinger, Aurélie Fischer, Laurent Malisoux, Hanen Samouda, Torsten Bohn, Maria Ruiz-Castell, Laetitia Huiart
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/fada0620fe1a4356a0fc65174288dcb6
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