Prevention of Cardiometabolic Syndrome in Children and Adolescents Using Machine Learning and Noninvasive Factors: The CASPIAN-V Study

Prevention of Cardiometabolic Syndrome in Children and Adolescents Using Machine Learning and Noninvasive Factors: The CASPIAN-V Study

Cardiometabolic syndrome (CMS) is a growing concern in children and adolescents, marked by obesity, hypertension, insulin resistance, and dyslipidemia. This study aimed to predict CMS using machine learning based on data from the CASPIAN-V study, which involved 14,226 participants aged 7–18 years, w...

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Bibliographic Details
Main Authors: Hamid Reza Marateb, Mahsa Mansourian, Amirhossein Koochekian, Mehdi Shirzadi, Shadi Zamani, Marjan Mansourian, Miquel Angel Mañanas, Roya Kelishadi
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Information
Subjects:
adolescent health
cardiometabolic risk
children
early diagnosis
machine learning
metabolic syndrome
Online Access:https://www.mdpi.com/2078-2489/15/9/564
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