Africa has the highest maternal mortality rate with gestational hypertension as the second leading cause of death among pregnant teenagers. Despite the utilization of Machine Learning techniques in maternal health research, there is a pressing need to develop more effective mechanisms for identifying teenage patients at risk of gestational hypertension.

The goal of this project is to develop an ML model to identify teenage patients at risk of gestational hypertension.The project will gather clinical datasets relating to teenage pregnancies from the Namibian context, train the dataset based on nine binary classification models and compare the prediction performance of the different models trained. This will provide treatment options at an early phase which could prevent progression into preeclampsia.

The PI of this project is Dr Gloria Iyawa, a Senior Lecturer in the Department of Informatics at Pan African Information Communication Technology Association (“PAICTA”). PAICTA is an organization that advocates for African ICT growth and economic development by fostering digital inclusion, collaboration, and increased co-operation in the ICT digital ecosystem throughout Africa. To stay up to date with this project, Check out their website