BUSINESS WIRE
Company to highlight how its ECG-AI™ algorithms enable earlier cardiovascular disease detection
Anumana to Showcase AI-Driven Cardiovascular Solutions at AHA and NAPCRG 2024
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Andrea Sampson
President/CEO, Sampson Public Relations Group
asampson@sampsonprgroup.com
Anumana, a leading AI-driven health technology company, will showcase its leadership in AI-powered cardiovascular solutions at the American Heart Association (AHA) Scientific Sessions 2024, booth #708, in Chicago, and at the North American Primary Care Research Group (NAPCRG) Annual Meeting in Quebec City.
“Empowering physicians with real-time, clinically meaningful insights is at the heart of Anumana’s mission,” said Maulik Nanavaty, CEO of Anumana. “We look forward to showcasing our ECG-AI algorithm, which uses a standard 12-lead ECG to detect low ejection fraction—a key indicator of heart failure. By transforming routine tests into tools that enable earlier diagnosis and treatment, we aim to elevate standards in cardiovascular care and improve patient outcomes.”
At the conferences, Anumana will feature its FDA-cleared ECG-AI™ Low Ejection Fraction (LEF) algorithm, which is currently available in the U.S. and was recently recognized in the CMS 2025 OPPS final rule. The company will also host expert panel discussions to highlight the role of AI in clinical care.
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Panel session: “The Future of AI in Cardiology: Trends, Expert Insights, and Panel Discussion”
- November 17 at 12:30 p.m. CT
- The session will explore the latest trends of AI/ML devices in cardiology, highlighting the journey of ECG-AI LEF from its initial concept to becoming an FDA-cleared Software as a Medical Device (SaMD). Experts will discuss the opportunities, challenges, and solutions shaping the future of AI in cardiology.
- Speakers: Samir Awasthi, MD, PhD; Heather Alger, PhD; Ambarish Pandey, MD; Mark Stampehl, MD
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Abstract presentation: “Deep Learning Enabled Electrocardiogram Aimed to Detect Coronary Artery Disease to Predict Atherosclerotic Cardiovascular Events in the Community”
- Presentation: November 16 at 10:20-10:25 a.m. CT
- Speaker: Jose R Medina-Inojosa, MD, MSc
- “Equity in Equations” Breakfast Symposium: November 17 at 6:30-8:00 a.m. CT
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Workshop topic: “Primary Care is the Next Frontier for AI Disruption: Low EF ECG-AI Algorithm Development as a Case Study”
- November 21 at 1:45-3:15 p.m. ET
- The 90-minute workshop will feature experts who will explore how AI innovations can be integrated into primary care workflows. Topics will cover recent advancements in health technology tools tailored for clinical care, the current state of AI-powered ECG tools, and essential considerations for evaluating and selecting health technology tools for primary care.
- Speakers: Heather Alger, PhD, MPH; Rowena Dolor, MD, MHS, MHS; David Rushlow, MD, MBOE; Chris Pullins, MD
Anumana’s ECG-AI platform includes a suite of algorithms designed to help clinicians detect cardiovascular diseases using ECG data. In addition to its FDA-cleared ECG-AI LEF algorithm, Anumana has also received FDA Breakthrough Device Designation for its pulmonary hypertension, cardiac amyloidosis, and hyperkalemia algorithms. The company’s AI tools unlock critical insights from ECGs to enhance the detection and management of heart disease.
About Anumana
Anumana is a leading AI-driven health technology company leveraging cutting-edge AI and industry-leading translational science to unlock the electrical language of the heart as never before. The company was founded by nference in collaboration with Mayo Clinic to leverage the clinical and technical expertise of both organizations to develop innovative ECG-AI technology into a clinically meaningful, medical-grade, and easy-to-use tool for clinicians to advance patient care. Anumana’s software-as-a-medical device (SaMD) ECG-AI™ solutions aim to detect diseases earlier using standard-of-care ECG readings, enabling clinicians to enhance and improve care with real-time AI insights. Anumana’s award-winning lead algorithm, ECG-AI™ LEF, is now available in the U.S. To learn more about how the algorithm can help clinicians identify LEF earlier and schedule a demo, visit us at ECG-AI LEF. For more information, visit www.anumana.ai or follow us on LinkedIn and X.
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