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Africa South of the Sahara

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Identifying Factors Associated with Neonatal Mortality in Sub-Saharan Africa using Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study aimed at identifying the factors associated with neonatal mortality. We analyzed the Demographic and Health Survey (DHS) datasets from 10 Sub-Saharan countries. For each survey, we trained machine learning models to identify women who had ...

Machine learning models for predicting the use of different animal breeding services in smallholder dairy farms in Sub-Saharan Africa.

Tropical animal health and production
This study is concerned with developing predictive models using machine learning techniques to be used in identifying factors that influence farmers' decisions, predict farmers' decisions, and forecast farmers' demands relating to breeding service. T...

Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa.

The Pan African medical journal
In sub-Saharan Africa, there is a significant unmet need for emergency care, with a shortage of trained providers. One model to increase the number of providers is to task-share: roles traditionally filled by clinicians are shared with lay workers wh...

Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa.

BMC pregnancy and childbirth
BACKGROUND: Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, ad...

Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm.

CPT: pharmacometrics & systems pharmacology
Warfarin remains the most widely prescribed oral anticoagulant in sub-Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine-learning tec...