CV Podcast: Reduced Lead Setting for Diagnostic ECG Interpretation Using Deep Learning Models


Reduced Lead Setting for Diagnostic ECG Interpretation Using Deep Learning Models

In this episode of the "Mayo Clinic Cardiovascular CME" podcast, guest Joel Xue, Ph.D., leader of the AI group of AliveCor and an adjunct professor of bioinformatics at Emory University, delves into the reduced lead setting for diagnostic ECG interpretation using deep learning models. Join the conversation as host Anthony Kashou, M.D., explores this approach to ECG analysis and how it compares to standard 12-lead ECG analysis.

During this episode, Dr. Xue and Dr. Kashou discuss:

  • Understanding reduced-12-lead ECG and its clinical value.
  • The main challenges in reduced lead ECG analysis.
  • Application of deep learning models in reduced lead ECG analysis.
  • Performance comparison with standard 12-lead ECG analysis.
  • Future research and clinical use.

Listen to the full episode here.

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Carly Mouzes (@cmouzes)

Carly Mouzes