Faisal Syed (UNC Cardiology): “How the machine-learning enhanced electrocardiogram can change the face of cardiovascular healthcare in North Carolina”

The application of machine learning (ML) techniques to electrocardiograms (ECG) has significantly enhanced the utility of the ECG as a biomarker of cardiac health and disease. Within a few years, there has been an explosion in different applications of ML-enhanced ECGs, from automation in diagnosis, to improved diagnostic accuracy to human interpretation, enhanced risk prediction and providing novel insights into disease mechanisms.  Although most of these applications have yet to reach clinical implementation, ECGs are a low cost, widely utilized and scalable technology which can be harnessed to improve cardiovascular outcomes and reduce healthcare inequity across North Carolina. This presentation will review the ML-enhanced ECG as a use case example of AI in healthcare, touch upon challenges underlying data access, protection and ownership, challenges with clinical implementation, and potential impact on cardiovascular healthcare.

For more information on this event, please contact Thomas Hofweber at hofweber@unc.edu.