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

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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Bibliographic Details
Main Authors: Guy Fagherazzi, Lu Zhang, Gloria Aguayo, Jessica Pastore, Catherine Goetzinger, Aurélie Fischer, Laurent Malisoux, Hanen Samouda, Torsten Bohn, Maria Ruiz-Castell, Laetitia Huiart
Format: Article
Language:English
Published: Nature Portfolio 2021-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-95487-5

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https://doi.org/10.1038/s41598-021-95487-5

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