Core Viewpoint - Sudden Cardiac Death (SCD) is a major global health issue, particularly in patients with Hypertrophic Cardiomyopathy (HCM), where current clinical guidelines show low performance and inconsistent accuracy in risk assessment [1][2]. Group 1 - SCD has an annual incidence of 50-100 cases per 100,000 people in North America and Europe, with ventricular arrhythmias being the primary mechanism [1]. - Implantable Cardioverter Defibrillators (ICDs) can effectively terminate arrhythmias and reduce mortality in high-risk patients when implanted preventively [1]. - The current risk stratification paradigm, based on Left Ventricular Ejection Fraction (LVEF) below 30%-35%, is primarily applicable to ischemic and dilated cardiomyopathy patients but fails to provide comprehensive risk assessment [2]. Group 2 - A recent study published by researchers from Johns Hopkins University introduced a multimodal AI model named MAARS (Multimodal Artificial intelligence for Ventricular Arrhythmia Risk Stratification) to predict arrhythmic death in HCM patients [3][4]. - MAARS utilizes a Transformer-based neural network that learns from electronic health records, echocardiograms, radiology reports, and contrast-enhanced cardiac MRI, which is a unique aspect of the model [8]. Group 3 - MAARS demonstrated an Area Under the Curve (AUC) of 0.89 in internal cohorts and 0.81 in external cohorts, significantly outperforming current clinical guidelines which have AUCs ranging from 0.27-0.35 (internal) and 0.22-0.30 (external) [10]. - Unlike clinical guidelines, MAARS shows fairness across different population subgroups, enhancing the transparency of AI predictions and identifying risk factors for further investigation [10]. - Overall, MAARS is a powerful and reliable clinical decision support tool for risk stratification of SCD in HCM patients, with potential to significantly improve clinical decision-making and patient care through integration with automated data extraction systems or as a concept validation for personalized patient care [10].