Predicting Childhood Obesity Based on Single and Multiple Well-Child Visit Data Using Machine Learning Classifiers

Predicting Childhood Obesity Based on Single and Multiple Well-Child Visit Data Using Machine Learning Classifiers

Childhood obesity is a public health concern in the United States. Consequences of childhood obesity include metabolic disease and heart, lung, kidney, and other health-related comorbidities. Therefore, the early determination of obesity risk is needed and predicting the trend of a child’s body mass...

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Bibliographic Details
Main Authors: Pritom Kumar Mondal, Kamrul H. Foysal, Bryan A. Norman, Lisaann S. Gittner
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
childhood obesity
machine learning
classification
BMI
well-child visit
Online Access:https://www.mdpi.com/1424-8220/23/2/759

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https://www.mdpi.com/1424-8220/23/2/759

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