Bias, Equity, and Reality: Issues When Using AI for ECG-based Diagnostics

In recent years, the health care industry has been increasingly adopting artificial intelligence (AI) technology to enhance patient care. In this episode of the "Mayo Clinic Cardiovascular CME" podcast, Gari Clifford, Ph.D., chair of Biomedical Informatics at Emory University, and Reza Sameni, Ph.D., associate professor of the Department of Biomedical Informatics at Emory University, join host Anthony Kashou, M.D., to share their insights on using AI for ECG-based diagnostics.

During the podcast, Dr. Clifford, Dr. Sameni, and Dr. Kashou discuss:

• Key barriers to building AI models from electrocardiogram data.
• Ways to mitigate bias in AI models beyond balancing data.
• The importance of addressing bias in AI models for ECG-based diagnostics and why this process goes much deeper than simply balancing data.
• Advice for health care professionals wanting to use AI on large volumes of ECGs.

Listen to the full episode here.

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