Artificial Intelligence Detects Hidden Heart Valve Issues from EKGs Early

Recent advancements in artificial intelligence (AI) have opened new avenues for early detection of heart valve disorders. Researchers from Imperial College London and the Imperial College Healthcare NHS Trust have developed an AI algorithm capable of analyzing standard electrocardiogram (EKG) readings to identify subtle electrical changes associated with hidden heart valve defects.

This innovative AI system can predict the risk of developing significant valvular heart diseases—such as regurgitation in the mitral, tricuspid, or aortic valves—well before symptoms appear or structural changes are observable through imaging techniques like echocardiograms. In clinical studies, the AI demonstrated an ability to accurately forecast the likelihood of future valvular issues in approximately 69% to 79% of cases, with high-risk individuals being up to 10 times more prone to develop these conditions.

The study, published in the European Heart Journal, involved training the AI model with nearly 1 million EKG and heart ultrasound records from over 400,000 Chinese patients. It was subsequently tested on a separate U.S. patient cohort, confirming its effectiveness across diverse populations and healthcare settings. This method allows for earlier intervention, potentially before the onset of symptoms such as shortness of breath, dizziness, fatigue, or palpitations, which are common signs of advanced heart disease.

Dr. Arunashis Sau, a lead researcher, emphasized that this approach could revolutionize the way clinicians monitor heart health. Instead of waiting for clinical symptoms or relying solely on costlier imaging tests, AI-enhanced EKG analysis offers a simple, accessible, and highly predictive tool for identifying at-risk individuals at an earlier stage.

The implications of this research are significant, especially considering the global prevalence of heart valve diseases—affecting approximately 41 million people worldwide, including 1.5 million in the U.K. Early detection can drastically improve outcomes by enabling prompt treatment, reducing hospitalizations, and preventing heart failure or death.

As the technology continues to develop, future work includes expanding AI models to predict other cardiovascular risks such as stroke, hypertension, and diabetes, further enhancing preventative cardiology. This collaborative effort illustrates the powerful role of international data sharing and AI in transforming healthcare practices around the world.