Predicting risk of obesity in overweight adults using interpretable machine learning algorithms

OBJECTIVE: To screen for predictive obesity factors in overweight populations using an optimal and interpretable machine learning algorithm. METHODS: This cross-sectional study was conducted between June 2011 and January 2012. The participants were randomly selected using a simple random sampling te...

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Detalles Bibliográficos
Autores principales: Lin, Wei, Shi, Songchang, Huang, Huibin, Wen, Junping, Chen, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Endocrinology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693451/
https://www.ncbi.nlm.nih.gov/pubmed/38047114
http://dx.doi.org/10.3389/fendo.2023.1292167

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693451/
https://www.ncbi.nlm.nih.gov/pubmed/38047114
http://dx.doi.org/10.3389/fendo.2023.1292167

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