Leveraging machine learning models for anemia severity detection among pregnant women following ANC: Ethiopian context.

Journal: BMC public health
PMID: 39696213

Abstract

BACKGROUND: Anemia during pregnancy is a significant public health concern, particularly in resource-limited settings. Machine learning (ML) offers promising avenues for improved anemia detection and management. This study investigates the potential of ML models in predicting anemia severity among pregnant women attending Antenatal Care (ANC) visits in Ethiopia.

Authors

  • Bekan Kitaw
    Faculty of Computing and Informatics, Jimma University, P.O. Box 378, Jimma, Ethiopia. bekan.mekonen@ju.edu.et.
  • Chera Asefa
    School of Electrical and Computer Engineering, Jimma University, P.O. Box 378, Jimma, Ethiopia.
  • Firew Legese
    Health Informatics, Ethiopian Public Health Institute, P.O. Box 1242, Addis Ababa, Ethiopia.

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