Predicting South Korean adolescents vulnerable to obesity after the COVID-19 pandemic using categorical boosting and shapley additive explanation values: A population-based cross-sectional survey

• Published in: Frontiers in pediatrics Vol. 10; p. 955339
• Main Author: Byeon, Haewon
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 21.09.2022
• Subjects: adolescent; CatBoost; COVID-19 pandemic; machine learning; obesity; Pediatrics

This study identified factors related to adolescent obesity during the COVID-19 pandemic by using machine learning techniques and developed a model for predicting high-risk obesity groups among South Korean adolescents based on the result.ObjectiveThis study identified factors related to adolescent...