Critical Transitions in Cardiac Systems: Towards better prediction and understanding using deep learning
A WICI Speaker Series event co-hosted with the Department of Applied Mathematics, Mathematical Biology Seminar Series
The human heart is a complex system that can undergo a critical transition to an abnormal rhythm, known as a cardiac arrhythmia. How to predict or assess the risk of cardiac arrhythmia in individual patients with heart disease is not clear. In this talk, Dr. Thomas Bury will demonstrate how deep learning can be combined with mathematical models of the heart to (i) improve prediction of an arrhythmia known as alternans, and (ii) discover mechanisms that can lead to arrhythmia. Methods are validated in vitro using heart cell aggregates and monolayers. Bury will argue that the rapid development of cardiac monitoring techniques is giving rise to exciting opportunities at the interface of cardiology and mathematics.
Dr. Thomas Bury is an applied mathematician, data scientist, and TEDx speaker, currently working in the Faculty of Medicine at McGill University. His research applies mathematics and artificial intelligence to the natural sciences, including medicine, ecology, and the climate. He is currently developing methods to better predict and classify cardiac arrhythmia.