Reduced Lead Setting for Diagnostic ECG Interpretation Using Deep Learning Models

Reduced Lead Setting for Diagnostic ECG Interpretation Using Deep Learning Models Guests: Joel Xue, Ph.D. Hosts: Anthony H. Kashou, M.D. (@anthonykashoumd) Joining us today to discuss what reduced-lead ECG analysis is, it's clinical value, some of its challenges, and how it compares to standard 12-lead ECG analysis is Joel Xue, Ph.D. Dr. Xue currently leads the AI group of AliveCor and is an adjunct professor of Bioinformatics department at Emory University, Atlanta, Georgia. Tune in to learn about using Deep learning models to reduce lead setting for diagnostic ECG interpretation. Specific topics discussed: What is reduced-12-lead ECG, and what is its clinical value? What are the main challenges for the reduced lead ECG analysis? How the Deep learning model method can be applied to reduced lead ECG analysis? Are the analysis performance comparable to the standard 12-lead ECG analysis? Next steps R&D and clinical use. Connect with Mayo Clinic's Cardiovascular Continuing Medical Education online at https://cveducation.mayo.edu or on Twitter @MayoClinicCV and @MayoCVservices. Facebook: MayoCVservices LinkedIn: Mayo Clinic Cardiovascular Services NEW Cardiovascular Education App:The Mayo Clinic Cardiovascular CME App is an innovative educational platform that features cardiology-focused continuing medical education wherever and whenever you need it. Use this app to access other free content and browse upcoming courses. Download it for free in Apple or Google stores today! No CME credit offered for this episode. Podcast episode transcript found here.