Core Viewpoint - The article discusses the increasing prevalence of Structural Heart Disease (SHD) and highlights the development of an AI screening tool, EchoNext, which can accurately identify patients with SHD from standard electrocardiograms (ECGs) [1][4][10]. Group 1: Overview of Structural Heart Disease - Structural Heart Disease (SHD) includes conditions affecting heart valves, walls, or chambers, impacting millions globally [1]. - Early detection of SHD can reduce mortality, treatment costs, and improve quality of life, but many patients are diagnosed late due to the lack of affordable screening tests [2]. Group 2: Development of EchoNext - Researchers from Columbia University and NewYork-Presbyterian Hospital developed EchoNext, an AI tool that analyzes ECG data to identify SHD patients with higher accuracy than human experts [3][4]. - EchoNext aims to provide a cost-effective method to determine which patients require further expensive echocardiogram examinations [7]. Group 3: Performance and Validation of EchoNext - The AI model was trained on over 1.2 million ECG-echocardiogram pairs from 230,000 patients to detect various forms of SHD [10]. - In a validation study across four healthcare systems, EchoNext demonstrated high accuracy in identifying SHD, including conditions like heart failure and valvular disease [12]. Group 4: Clinical Application and Results - In a study involving nearly 85,000 patients who had not undergone echocardiograms, EchoNext identified over 7,500 individuals (9%) at high risk for undiagnosed SHD [13]. - Among those identified as high-risk, 55% underwent their first echocardiogram, with nearly 75% diagnosed with SHD, indicating a positive rate twice that of those without AI assistance [14]. Group 5: Comparison with Human Experts - A comparison of EchoNext with 13 cardiologists showed that while AI assistance improved the accuracy of human assessments, EchoNext outperformed human experts with an accuracy of 77.3%, sensitivity of 72.6%, and specificity of 80.7% [16][17].