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Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)

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Published in:PLOS Global Public Health
Format: Online Article RSS Article
Published: 2026
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container_title PLOS Global Public Health
description
discipline_display Health and Safety
discipline_facet Health and Safety
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genre Journal Article
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journal_source_facet PLOS Global Public Health
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publishDate 2026
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spellingShingle Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)
Health and Safety
General
Health and Safety
sub_discipline_display General
sub_discipline_facet General
subject_display Health and Safety
General
Health and Safety
subject_facet Health and Safety
General
Health and Safety
title Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)
title_alt Uso de aprendizaje automático explicable en la clasificación de riesgo de parto por cesárea: Un análisis transversal de Encuestas Demográficas y de Salud de diez países del África subsahariana (2016–2024)
Utilisation de l'apprentissage automatique explicable dans la classification des risques de césarienne : une analyse transversale des enquêtes démographiques et de santé de dix pays d'Afrique subsaharienne (2016–2024)
Uso de aprendizado de máquina explicável na classificação de risco de parto por cesariana: Uma análise transversal de Inquéritos Demográficos e de Saúde de dez países da África Subsaariana (2016–2024)
title_auth Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)
title_es_txt Uso de aprendizaje automático explicable en la clasificación de riesgo de parto por cesárea: Un análisis transversal de Encuestas Demográficas y de Salud de diez países del África subsahariana (2016–2024)
title_fr_txt Utilisation de l'apprentissage automatique explicable dans la classification des risques de césarienne : une analyse transversale des enquêtes démographiques et de santé de dix pays d'Afrique subsaharienne (2016–2024)
title_full Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)
title_fullStr Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)
title_full_unstemmed Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)
title_pt_txt Uso de aprendizado de máquina explicável na classificação de risco de parto por cesariana: Uma análise transversal de Inquéritos Demográficos e de Saúde de dez países da África Subsaariana (2016–2024)
title_short Use of explainable machine learning in risk classification of Cesarean section delivery: A cross-sectional analysis of Demographic and Health Surveys from ten Sub-Saharan African countries (2016–2024)
title_sort use of explainable machine learning in risk classification of cesarean section delivery: a cross-sectional analysis of demographic and health surveys from ten sub-saharan african countries (2016–2024)
topic Health and Safety
General
Health and Safety
url https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0006613