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

OBJECTIVE: 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. MATERIALS AND METHODS: This study analyzed 50,858...

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Detalles Bibliográficos
Autor principal: Byeon, Haewon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Pediatrics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532523/
https://www.ncbi.nlm.nih.gov/pubmed/36210956
http://dx.doi.org/10.3389/fped.2022.955339

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532523/
https://www.ncbi.nlm.nih.gov/pubmed/36210956
http://dx.doi.org/10.3389/fped.2022.955339

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