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Development and Validation of Metabolic Syndrome Prediction and Classification-Pathways using Decision Trees

Metabolic syndrome (MetS) is a constellation of cardiometabolic predictor variables that when presented in tandem increases the risk of cardiovascular disease (CVD) and insulin resistance [1,2]. The prevalence of this classification affects approximately 1 in 3 adults in the United States [3]. Due to the high prevalence of this syndrome, proper identification of persons with MetS is imperative in order to prevent and/or modify the multiple predictor variables associated with CVD related morbidity and mortality as well as its high healthcare costs [1,2,4,5]. Furthermore, utilization of pathways for MetS classification could guide health education professional interventions before the onset of related morbidity and mortality

Citation: Miller B, Fridline M (2015) Development and Validation of Metabolic Syndrome Prediction and Classification-Pathways using Decision Trees. J Metabolic Synd 4:173.

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