Exploring machine learning algorithms for predicting fertility preferences among reproductive age women in Nigeria.

Journal: Frontiers in digital health
Published Date: Jan 16, 2025

Abstract

BACKGROUND: Fertility preferences refer to the number of children an individual would like to have, regardless of any obstacles that may stand in the way of fulfilling their aspirations. Despite the creation and application of numerous interventions, the overall fertility rate in West African nations, particularly Nigeria, is still high at 5.3% according to 2018 Nigeria Demographic and Health Survey data. Hence, this study aimed to predict the fertility preferences of reproductive age women in Nigeria using state-of-the-art machine learning techniques.

Authors

  • Zinabu Bekele Tadese
    Department of Health Informatics, College of Medicine and Health Science, Samara University, Samara, Ethiopia.
  • Teshome Demis Nimani
    Department of Epidemiology and Biostatistics, School of Public Health College of Medicine and Health Science, Haramaya University, Harar, Ethiopia.
  • Kusse Urmale Mare
    Department of Nursing, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.
  • Fetlework Gubena
    Department of Public Health, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia.
  • Ismail Garba Wali
    Department of Demography & Social Statistics, Federal University, Birnin-Kebbi, Kebbi State, Nigeria.
  • Jamilu Sani
    Department of Demography & Social Statistics, Federal University, Birnin-Kebbi, Kebbi State, Nigeria.

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