Anumana develops AI-driven ECG algorithms that enable early detection of cardiovascular diseases, utilizing a vast dataset of electrophysiological data and patient outcomes. By facilitating timely diagnosis and intervention, Anumana aims to reduce the healthcare burden associated with undiagnosed heart conditions.
Funding
$89.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Cardiovascular diseases often remain undiagnosed until symptoms become severe, leading to life-threatening events and a significant healthcare burden. Traditional diagnostic methods may not detect subtle indicators of underlying heart conditions in their early stages.
Solution
Anumana is a health technology company that develops AI-driven solutions for the early detection of cardiovascular diseases. By applying advanced machine-learning algorithms to electrocardiogram (ECG) data, Anumana's technology identifies subtle signals indicative of hidden heart conditions. These algorithms analyze electrophysiological data, longitudinal patient histories, and outcomes to provide clinicians with insights for earlier diagnosis and intervention. Anumana's solutions aim to improve procedure accuracy, reduce procedure times, improve medication management, and improve patient safety and outcomes. The company's portfolio includes ECG-AI algorithms for early disease detection and EGM-AI algorithms to improve electrophysiology (EP) procedures.
Target Audience
Anumana's primary target audience includes cardiologists, electrophysiologists, primary care physicians, and other healthcare providers involved in the diagnosis and treatment of cardiovascular diseases.
Features
- AI-powered algorithms that analyze ECG data to detect subtle indicators of cardiovascular diseases
- Access to a large dataset of electrophysiological data, longitudinal patient history, and outcomes
- Algorithms for early detection of low ejection fraction, pulmonary hypertension, and cardiac amyloidosis
- Algorithms to improve the accuracy, speed, and safety of electrophysiology procedures
- Software solutions that integrate with existing clinical workflows and EMR systems
- Algorithms validated by peer-reviewed publications
- Algorithms that have received FDA Breakthrough Device Designation