Predicting and identifying factors associated with undernutrition among children under five years in Ghana using machine learning algorithms

Eric Komla Anku and Henry Ofori Duah

PLOS ONE, 2024, vol. 19, issue 2, 1-16

Abstract: Background: Undernutrition among children under the age of five is a major public health concern, especially in developing countries. This study aimed to use machine learning (ML) algorithms to predict undernutrition and identify its associated factors. Methods: Secondary data analysis of the 2017 Multiple Indicator Cluster Survey (MICS) was performed using R and Python. The main outcomes of interest were undernutrition (stunting: height-for-age (HAZ)

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0296625

DOI: 10.1371/journal.pone.0296625

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