Meet the Data Science Summer Institute class of 2024.
Students tackled a shared problem in cardiology: The electrocardiogram (ECG) provides a noninvasive, cost-effective diagnosis of heart conditions, but the standard 12-lead ECG is inadequate for mapping the heart’s electrical activity in sufficient detail for many clinical applications. Students explored a data-driven approach to reconstructing electro-anatomical maps of the heart at clinically relevant resolutions, combining input from the standard 12-lead ECG with advanced machine learning techniques.
