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Eliyas Addisu

As seen in: Biomed Central (BMC)
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Articles

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 | BMC Public Health | Full Text

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By Eden Amare Yitbarek, Eliyas Addisu, Gabrela Yimer, Fetlework Gubena
| Biomed Central (BMC)
The study used data from recent surveys conducted in 27 SSA countries between 2016 and 2024 G.C. These countries were Angola, Benin, Burkina Faso, Burundi, Cameroon, Côte d’Ivoire, Ethiopia, Gabon, Ghana, Gambia, Guinea, Kenya, Liberia, Lesotho, Madagascar, Malawi, Mali, Mauritania, Mozambique, Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Tanzania, Uganda, and Zambia.
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