Using Machine Learning to Detect Congenital Heart Disease in Prenatal Ultrasound Imaging

Project Description 

This project explores the use of machine learning - particularly deep learning  - techniques to improve prenatal detection rates of Congenital Heart Disease (CHD) in resource-constrained settings like South Africa. This research investigates the applicability and reliability of a binary classification model in these settings, with the aim of assisting sonographers, paediatric cardiologists, and physicians with a decision-making tool - therefore improving detection rates. 

TEAM