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

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 from ORISC...

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Detalles Bibliográficos
Autores principales: Fagherazzi, Guy, Zhang, Lu, Aguayo, Gloria, Pastore, Jessica, Goetzinger, Catherine, Fischer, Aurélie, Malisoux, Laurent, Samouda, Hanen, Bohn, Torsten, Ruiz-Castell, Maria, Huiart, Laetitia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346462/
https://www.ncbi.nlm.nih.gov/pubmed/34362963
http://dx.doi.org/10.1038/s41598-021-95487-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346462/
https://www.ncbi.nlm.nih.gov/pubmed/34362963
http://dx.doi.org/10.1038/s41598-021-95487-5

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