Optimizing machine learning models for predicting anemia among under-five children in Ethiopia: insights from Ethiopian demographic and health survey data.

Journal: BMC pediatrics
PMID: 40264060

Abstract

BACKGROUND: Healthcare practitioners require a robust predictive system to accurately diagnose diseases, especially in young children with conditions such as anemia. Delays in diagnosis and treatment can have severe consequences, potentially leading to serious complications and childhood mortality. By leveraging machine learning methods with extensive datasets, valuable and scientifically sound insights can be generated to address pressing health and healthcare-related challenges.

Authors

  • Ali Yimer
    Department of Public Health, College of Health Sciences, Woldia University, Woldia, Ethiopia.
  • Hassen Ahmed Yesuf
    Department of Biomedical Science, College of Health Sciences, Woldia University, Woldia, Ethiopia.
  • Sada Ahmed
    Department of Information Technology, Institute of Technology, Woldia University, Woldia, Ethiopia.
  • Alemu Birara Zemariam
    Department of Pediatrics and Child Health Nursing, School of Nursing, College of Medicine and Health Science, Woldia University, Woldia, Ethiopia.
  • Endris Mussa
    Department of Software Engineering, College of Informatics, Wollo University, Kombolcha, Ethiopia.
  • Nurye Sirage
    Department of Midwifery, College of Health Sciences, Woldia University, Woldia, Ethiopia.
  • Adem Yesuf
    Department of Midwifery, College of Health Sciences, Woldia University, Woldia, Ethiopia.
  • Abdulaziz Kebede Kassaw
    Department of Health Informatics, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.

Keywords

External Resources

Popular Topics
Recent Journals