Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa

Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa

BackgroundPregnancy loss is a significant public health issue globally, particularly in Sub-Saharan Africa (SSA), where maternal health outcomes continue to be a major concern. Despite notable progress in improving maternal health, pregnancy-related complications, including s due to miscarriages, st...

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Bibliographic Details
Main Authors: Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Global Women's Health
Subjects:
prediction
reproductive-aged women
pregnancy loss
machine learning
Sub-Saharan Africa
Online Access:https://www.frontiersin.org/articles/10.3389/fgwh.2025.1456238/full
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