Device Agnostic Artificial Intelligence-based Analysis of Ambulatory ECG Recordings

Device Agnostic Artificial Intelligence-based Analysis of Ambulatory ECG Recordings Guest: Alan Kennedy, Ph.D. Hosts: Anthony H. Kashou, M.D. (@anthonykashoumd) Joining us today to discuss Device Agnostic Artificial Intelligence-based Analysis of Ambulatory ECG Recordings is Alan Kennedy, Ph.D., biomedical engineer by training, and holds a Ph.D. in the application of deep learning for the diagnosis of medical conditions from Ulster University. His current work focuses on developing wearable ECG patch technology and deep learning algorithms for ECG classification. Specific topics discussed: What is meant by device agnostic ECG interpretation How can AI enable device agnostic ECG interpretation over traditional ECG interpretation software How will the use of AI-ECG interpretation affect the future of Cardiology 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.