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Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis
Research article (BMC Public Health, 2025) · cited 16× · AI/ML
Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis
Summary
Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis is a scholarly article[1].
Key Facts
Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis. Retrieved May 24, 2026, from https://4ort.xyz/entity/application-of-the-random-forest-algorithm-to-predict-skilled-birth-attendance-and-identify-determinants-among-reproduct
MLA“Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/application-of-the-random-forest-algorithm-to-predict-skilled-birth-attendance-and-identify-determinants-among-reproduct.
BibTeX@misc{4ortxyz_application-of-the-random-forest-algorithm-to-predict-skilled-birth-attendance-and-identify-determinants-among-reproduct_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis}}, year = {2026}, url = {https://4ort.xyz/entity/application-of-the-random-forest-algorithm-to-predict-skilled-birth-attendance-and-identify-determinants-among-reproduct}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis — https://4ort.xyz/entity/application-of-the-random-forest-algorithm-to-predict-skilled-birth-attendance-and-identify-determinants-among-reproduct (retrieved 2026-05-24)
