Predicting home delivery and identifying its determinants among women aged 15–49 years in sub-Saharan African countries using a Demographic and Health Surveys 2016–2023: a machine learning algorithm
Abstract Background Birth-related mortality is significantly increased by home births without skilled medical assistance during delivery, presenting a major risk to the public’s health. The objective of this study is to predict home delivery and identify the determinants using machine learning algor...
Saved in:
Main Authors: | Adem Tsegaw Zegeye, Binyam Chaklu Tilahun, Makida Fekadie, Eliyas Addisu, Birhan Wassie, Berihun Alelign, Mequannet Sharew, Nebebe Demis Baykemagn, Abdulaziz Kebede, Tirualem Zeleke Yehuala |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-01-01
|
Series: | BMC Public Health |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12889-025-21334-1 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa
by: Tirualem Zeleke Yehuala, et al.
Published: (2025-02-01) -
Simulation-based probabilistic-harmonic load flow for the study of DERs integration in a low-voltage distribution network
by: Cristian Cadena-Zarate, et al.
Published: (2024-02-01) -
Omilayers: a Python package for efficient data management to support multi-omic analysis
by: Dimitrios Kioroglou
Published: (2025-02-01) -
Scilab-RL: A software framework for efficient reinforcement learning and cognitive modeling research
by: Jan Benad, et al.
Published: (2025-02-01) -
Multi-functional code for hydrogen isotopes transport analyses: verification & validation against fusion-relevant applications
by: F. Hattab, et al.
Published: (2025-01-01)