Leveraging Machine Learning and Genetic Risk Scores for the Prediction of Metabolic Syndrome in Children with Obesity

Background and objectives: Obesity is a growing global epidemic, associated with increased cardiometabolic disorders. Metabolic syndrome (MS) is defined by altered insulin, blood pressure, glucose, and lipid levels. Pubertal children with obesity are highly susceptible to developing MS, necessitatin...

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Autori principali:	Concepción M. Aguilera, Mireia Bustos-Aibar, Augusto Anguita-Ruiz, Álvaro Torres-Martos, Gloria Bueno, Rosaura Leis, Jesús Alcalá-Fernández
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2024-02-01
Serie:	Proceedings
Soggetti:	machine learning genetics gene-environment interaction genetic markers childhood obesity polygenetic risk scores
Accesso online:	https://www.mdpi.com/2504-3900/91/1/377
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