Finding heart problems using Artificial Intelligence

 Detecting structural heart problems in asymptomatic individuals has been a challenge, but a researcher at the Yale School of Medicine has developed a solution using artificial intelligence (AI). 

    Dr. Rohan Khera, clinical director of the Center for Health Informatics and Analytics, has discovered that AI can analyze electrocardiograms (ECGs) to identify heart problems that may not be visible to the naked eye. 

    Left ventricular systolic dysfunction, a structural heart disorder that reduces the heart's ability to pump blood, can be detected before symptoms arise, reducing the risk of heart failure and premature death. 

    Khera's team has developed a technology that can identify signatures of structural heart disorders from ECG data using AI and deep learning. 

    With approximately 100 million ECGs performed in the United States each year, analyzing this data using AI has the potential to accurately identify individuals with heart disorders. 

     The Yale study has been validated in multiple locations, and Khera's approach has shown promising results. As AI and ECG technology continue to advance, screening for heart disorders using ECGs is expected to become more common, and the capability of AI to identify heart conditions that humans may miss is an exciting development in the field of cardiology.

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