Nov 4, 2025

Viz.ai, the leader in AI-powered disease detection and intelligent care coordination, today announced new clinical data demonstrating how Viz HCM enables faster, accurate detection of hypertrophic cardiomyopathy (HCM), to help ensure that more patients are identified. Two studies, which will be presented at the American Heart Association (AHA) Scientific Sessions 2025, show Viz.ai's real-world ability to identify more patients with HCM years earlier than current standard of care, expanding and accelerating access to life-saving care. The University of Texas Medical Branch study, “Improving Early Detection of Hypertrophic Cardiomyopathy Using Viz-HCM: A Quality Improvement Initiative Leveraging Artificial Intelligence-Assisted EKG Screening, ” evaluated the real-world impact of Viz HCM in a system-wide implementation initiative across four campuses and 22 outpatient clinics. The algorithm identified 48 newly diagnosed HCM patients during a five-month prospective screening period and reduced the average time from ECG flag to diagnostic confirmation to just 37 days, compared to years-long delays reported historically. Investigators concluded that Viz HCM significantly accelerated detection and individualized risk stratification timelines across the health system. “Implementation of Viz HCM allowed us to find new HCM patients faster and streamline their care pathways,” said Omar M. Abdelfattah, MD, lead investigator at the University of Texas Medical Branch. “This project shows how AI can be seamlessly integrated into the ECG workflow to improve detection, risk assessment, and coordination across the care continuum.” In the University of Virginia study, “Advanced Diagnosis of Hypertrophic Cardiomyopathy with AI-ECG and Differences Based on Ethnicity and HCM Subtype, ” published in Journal of Clinical Medicine, investigators retrospectively analyzed 3,499 ECGs from 404 patients using Viz.ai's deep neural network algorithm. The study found that 34% of HCM patients could have been identified before clinical diagnosis—some as early as 16.3 years earlier. Notably, Black patients were more likely than White patients to have an AI-based diagnosis before their clinical diagnosis, underscoring the potential of AI to improve equity in disease detection. “Our findings highlight how AI-ECG could fundamentally change the timeline of diagnosis for HCM,” said Michael Ayers, MD, Director of the HCM Center of Excellence at University of Virginia. “By flagging subtle ECG changes that precede symptoms, Viz HCM could help clinicians identify at-risk patients years earlier, potentially improving outcomes and addressing equity gaps in cardiovascular care.” Viz HCM uses artificial intelligence to analyze standard 12-lead electrocardiograms (ECGs) across a health system to detect patterns consistent with hypertrophic cardiomyopathy. When a suspected case is identified, the software automatically notifies the appropriate care team to ensure timely follow-up and diagnosis. Viz's ECG AI technology is already deployed at leading health institutions including Cleveland Clinic , Mount Sinai , and UCSD , and has screened more than three million patients to date. Viz HCM received De Novo authorization from the U.S. Food and Drug Administration (FDA) in August 2023, creating a new regulatory category for cardiovascular machine learning-based notification software, and is associated with newly established Category III CPT codes (0764T and 0765T) for AI-enabled ECG analysis to detect cardiac pathology such as HCM. The Centers for Medicare & Medicaid Services (CMS) has published a national payment rate of $128.90, effective January 1, 2025; actual reimbursement may vary by payer and setting. “Hypertrophic cardiomyopathy is one of the most common genetic heart diseases, yet it frequently goes undiagnosed or misdiagnosed for years,” said Jamie Stern, Senior Director, Clinical Operations & Strategy at Viz.ai. “These new data from UVA and UTMB reinforce how embedding AI into the ECG workflow can make a measurable difference in finding HCM earlier, improving equity in diagnosis, and accelerating access to specialized care. With proven clinical impact and rapid health-system adoption across the nation, Viz.ai is empowering clinicians to catch disease earlier and save more lives.” To learn more about Viz HCM, visit viz.ai/hcm or meet the Viz.ai team at AHA Scientific Sessions 2025. Lewontin, M., et al. (2025). Advanced Diagnosis of Hypertrophic Cardiomyopathy with AI-ECG and Differences Based on Ethnicity and HCM Subtype. Journal of Clinical Medicine, 14(13):4718. doi:10.3390/jcm14134718 Abdelfattah, O.M., et al. (2025). Improving Early Detection of Hypertrophic Cardiomyopathy Using Viz-HCM: A Quality Improvement Initiative Leveraging Artificial Intelligence-Assisted EKG Screening. Abstract accepted for presentation at the American Heart Association (AHA) Scientific Sessions 2025, Chicago, IL, November 7–10, 2025 Desai, M. Y., et al. (2025). Real-world artificial intelligence–based electrocardiographic analysis to diagnose hypertrophic cardiomyopathy. Journal of the American College of Cardiology: Clinical Electrophysiology, 11(6). https://doi.org/10.1016/j.jacep.2025.02.024 Lampert, J., et al. (2025). A multicenter, prospective cohort pilot study on the clinical implementation and utilization of an AI-based ECG tool for HCM detection and care coordination. Journal of the American College of Cardiology, 85(12 Suppl), S?–S?. https://doi.org/10.1016/S0735-1097(25)01831-5 Meyer, BC., et al. (2023). Artificial intelligence‐based electrocardiographic screening in hypertrophic cardiomyopathy: A retrospective multicenter study. Journal of Clinical Medicine, 14(13), 4718. https://doi.org/10.3390/jcm14134718 About Viz.ai Viz.ai is the leader in AI-powered care coordination and clinical workflow solutions, deployed in over 1,800 hospitals across the U.S and trusted by most of the top life sciences companies. Its platform uses artificial intelligence to detect diseases earlier, synchronize care teams, and ensure patients get to the right treatment faster. Viz.ai was the first company awarded CMS reimbursement for AI and ranked the #1 Healthcare AI Platform by hospitals and health systems in the Black Book Research survey, setting the standard for innovation in healthcare. For more information visit Viz.ai View source version on businesswire.com: https://www.businesswire.com/news/home/20251104915763/en/ Contacts Media Contacts Carolyn Jones carolyn.jones@viz.ai Daniel Yunger / Daniel Hoadley daniel.yunger@kekstcnc.com daniel.hoadley@kekstcnc.com