Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms

• Main Authors: Siy Van, Vanessa T, Antonio, Victor A, Siguin, Carmina P, Gordoncillo, Normahitta P., Sescon, Joselito T., Go, Clark C, Miro, Eden Delight
• 格式: text
• 出版: Archīum Ateneo 2022
• 主題: Nutrition; Machine learning; Philippines; Random forest; Prediction; Energy; Classification; Mathematics; Medicine and Health Sciences
• 在線閱讀: https://archium.ateneo.edu/mathematics-faculty-pubs/213; https://doi.org/10.1016/j.nut.2021.111571

Objectives This study aimed to compare the accuracy of four machine-learning (ML) algorithms, using two classification schemes, to predict undernutrition based on individual and household risk factors. Methods Data on public-school children were collected from a rural province (310 children) and a...