Reconstructing Inequality in Maternal Health: Imputation-enhanced Machine Learning Models for Global ANC4 Performance

Authors

Felix O. Mettle (ORCID: https://orcid.org/0000-0003-2160-0198)
Francis Ayiah-Mensah (ORCID: https://orcid.org/0000-0002-5672-9293)
Asiedu Kokuro
Samuel Kwame Okai

Institutions

University of Ghana (GH)
Takoradi Technical University (GH)

Publication Details

Published: 2026-01-02
DOI: https://doi.org/10.9734/arjgo/2026/v9i1310
Primary Topic: Global Maternal and Child Health
Type: article
Field-Weighted Citation Impact: 0.00

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article

Reconstructing Inequality in Maternal Health: Imputation-enhanced Machine Learning Models for Global ANC4 Performance

Felix O. Mettle, Francis Ayiah-Mensah, Asiedu Kokuro, Samuel Kwame Okai

Jan 2, 2026

Global Maternal and Child Health

article

Reconstructing Inequality in Maternal Health: Imputation-enhanced Machine Learning Models for Global ANC4 Performance

Felix O. Mettle, Francis Ayiah-Mensah, Asiedu Kokuro, Samuel Kwame Okai

January 2, 2026article en

Abstract

No abstract available for this paper.

Vol. 9(1)

University of Ghana (GH), Takoradi Technical University (GH)

Gender equality

Openalex Percentile: Top 97%

Global Maternal and Child Health

DOI Source OpenAlex

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Reconstructing Inequality in Maternal Health: Imputation-enhanced Machine Learning Models for Global ANC4 Performance — Felix O. Mettle, Francis Ayiah-Mensah, et al. · (2026) | TGRS Research Map | TGRS