Doha: A new study published in Nature reveals that an artificial intelligence tool named EchoNext could revolutionize early detection of structural heart diseases by analyzing traditional electrocardiogram (ECG) scans. Led by Dr. Pierre Elias from Columbia University's Vagelos College of Physicians and Surgeons, the research team found that the tool can interpret ECG data to identify patients who may require further echocardiographic (echo) testing-the current standard for diagnosing structural heart defects such as valve disorders or thickened cardiac tissue. According to Qatar News Agency, in medical school, Elias stated that they were taught that ECGs couldn't detect structural heart disease, but AI is rewriting that rule, turning this simple test into a powerful screening tool. Researchers highlighted that EchoNext offers a cost-effective method to guide referrals for more expensive echo exams, improving early detection rates and reducing financial burdens. The study compared the tool's performance with diagnoses made by 13 cardiologists who manually reviewed 3,200 ECGs. While the physicians achieved an average diagnostic accuracy of 64 percent, EchoNext reached 77 percent. Globally, an estimated 64 million people suffer from heart failure and 75 million from valve diseases. In the United States alone, the annual costs associated with these conditions exceed $100 billion.