Identifying factors associated with central obesity in school students using artificial intelligence techniques

OBJECTIVES: We, in a large survey of school students from Beijing, aimed to identify the minimal number of promising factors associated with central obesity and the optimal machine-learning algorithm. METHODS: Using a cluster sampling strategy, this cross-sectional survey was conducted in Beijing in...

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Detalles Bibliográficos
Autores principales: Zhang, Yicheng, Wang, Qiong, Xue, Mei, Pang, Bo, Yang, Min, Zhang, Zhixin, Niu, Wenquan
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/PMC9748186/
https://www.ncbi.nlm.nih.gov/pubmed/36533227
http://dx.doi.org/10.3389/fped.2022.1060270

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748186/
https://www.ncbi.nlm.nih.gov/pubmed/36533227
http://dx.doi.org/10.3389/fped.2022.1060270

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