Use of CHAID Decision Trees to Formulate Pathways for the Early Detection of Metabolic Syndrome in Young Adults

Metabolic syndrome (MetS) in young adults (age 20–39) is often undiagnosed. A simple screening tool using a surrogate measure might be invaluable in the early detection of MetS. Methods. A chi-squared automatic interaction detection (CHAID) decision tree analysis with waist circumference user-specif...

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Detalles Bibliográficos
Autores principales: Miller, Brian, Fridline, Mark, Liu, Pei-Yang, Marino, Deborah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003739/
https://www.ncbi.nlm.nih.gov/pubmed/24817904
http://dx.doi.org/10.1155/2014/242717

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003739/
https://www.ncbi.nlm.nih.gov/pubmed/24817904
http://dx.doi.org/10.1155/2014/242717

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