Causal machine learning models for predicting low birth weight in midwife-led continuity care intervention in North Shoa Zone, Ethiopia

Causal machine learning models for predicting low birth weight in midwife-led continuity care intervention in North Shoa Zone, Ethiopia

Abstract Background Low birth weight (LBW) is a critical global health issue that affects infants disproportionately, particularly in developing countries. This study adopted causal machine learning (CML) algorithms for predicting LBW in newborns, drawing from midwife-led continuity care (MLCC). Met...

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Bibliographic Details
Main Authors: Wudneh Ketema Moges, Awoke Seyoum Tegegne, Aweke A. Mitku, Esubalew Tesfahun, Solomon Hailemeskel
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Low Birth Weight
ATE
Machine learning
Causal machine learning
Meta–learner
Online Access:https://doi.org/10.1186/s12911-025-02917-9
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