Machine Learning in Predicting Child Malnutrition: A Meta-Analysis of Demographic and Health Surveys Data.

Journal: International journal of environmental research and public health
PMID: 40238576

Abstract

BACKGROUND: Childhood malnutrition remains a significant global public health concern. The Demographic and Health Surveys (DHS) program provides specific data on child health across numerous countries. This meta-analysis aims to comprehensively assess machine learning (ML) applications in DHS data to predict malnutrition in children.

Authors

  • Bhagyajyothi Rao
    Department of Applied Statistics & Data Science, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal 576104, India.
  • Muhammad Rashid
    Department of Computer Engineering, Umm Al-Qura University, Makkah, Saudi Arabia.
  • Md Gulzarull Hasan
    Department of Applied Statistics & Data Science, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal 576104, India.
  • Girish Thunga
    Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal 576104, India. Electronic address: girish.thunga@manipal.edu.

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