Harnessing industry-leading AI and translational science to decode electrical signals from the heart as never before, empowering healthcare providers to improve patient care throughout the cardiac clinical pathway
Listen to Dr. Paul Friedman, a Professor of Medicine and Chair of the Department of Cardiovascular Medicine at Mayo Clinic and Anumana advisor, discuss the potential of AI algorithms in advancing early diagnosis and intervention in cardiology.
Serious cardiovascular diseases affect millions of people worldwide, often going undiagnosed until symptoms advance and patients deteriorate. Unfortunately, these conditions can remain undiagnosed until the patient suffers a life-threatening event. Hidden and undiagnosed cardiovascular diseases can often be treated through available therapeutics and medical devices. Innovations enabling earlier diagnoses could address this unmet medical need and empower healthcare providers to intervene with beneficial treatments.
Millions of people suffer from cardiac arrhythmias, which can be a major risk of stroke and heart failure. The demand for electrophysiology (EP) procedures has been increasing rapidly but efficacy largely depends on experience and intuition, and repeat procedures are common. While large amounts of data are generated in real- time during the procedure, EP labs so far have not leveraged the power of AI interpretation. Deep-learning innovations could enable improved EP procedure accuracy and reduced procedure time, empowering providers to meet the growing demand with improved patient safety and outcomes.
Anumana leverages nference’s proprietary nSights real-world evidence generation platform, built on data from leading health systems, to combine unparalleled longitudinal structured and unstructured electronic medical record data with diagnostic and interventional ECGs and EGMs. By applying AI techniques to these electrical signals from the heart, the company has uncovered clinically critical electrical signatures and patterns unrecognizable to the human eye. The resulting software products can be integrated into routine clinical practice for earlier disease diagnosis and in-procedure decision making.
With a leading position in developing AI-enabled ECG algorithms, Anumana’s acquisition of NeuTrace in 2022 paved the way for a combined development capability in cardiac electrophysiology spanning the entire cardiac care continuum, from disease detection to in-procedure, interventional solutions.
Today, Anumana’s research is demonstrating that care teams working with AI-enabled tools can diagnose otherwise hidden conditions earlier than ever before and uncover actionable insights to potentially improve EP procedures. With clinical decision support tools, Anumana aims to help physicians identify missing treatments and avoid unnecessary interventions. Anumana is committed to bringing these software solutions to routine clinical practice with significant progress in software development and coding for reimbursement.
Learn about the new study by Mayo Clinic that uses a modified version of Anumana’s 12-lead ECG algorithm to detect left ventricular dysfunction using AI-enabled ECGs from the Apple Watch.Stat
May 1, 2022