Transforming How We Diagnose Hearth Disease
At IDLab, we are leveraging our data science expertise to transform how we diagnose heart diseases.
Our researchers finished among the winners of US 2nd National Data Science Bowl (on Kaggle.com) with a machine learning algorithm to automatically determine cardiac volumes from MRI scans. In 2015, this team also won the “Deep Sea” challenge , out of 1049 teams, in the 1st National Data Science Bowl.
The goal was to estimate minimum (end-systolic) and maximum (end-diastolic) volumes of the left ventricle from a set of MRI-images taken over one heartbeat, as these volumes are used by practitioners to compute an ejection fraction: fraction of outbound blood pumped from the heart with each heartbeat. This measurement can predict a wide range of cardiac problems. For a skilled cardiologist analysis of MRI scans can take up to 20 minutes. Automating this process enables MRI scanners to evolve from imaging devices towards cloud-assisted, smart tools in the process of diagnosing heart diseases.
Read more about IDLab’s solution.