RESEARCH TRIANGLE PARK, NC and TORONTO, CANADA, September 27, 2017 — Analytics 4 Life, a digital health company applying the power of artificial intelligence to develop solutions that improve existing care pathways, today announced it has completed a $25 million Series B financing. This unique financing event was supported by an international syndicate of accredited investors, including physicians, healthcare professionals, and medical device experts. The Company’s novel cardiac imaging technology is under clinical investigation to help physicians assess the presence of coronary artery disease (CAD) using intrinsic signals scanned from the body without radiation, contrast agents, or cardiac stress.

“Heart disease is the leading cause of death globally, with 1 in 7 deaths in the U.S. attributed to CAD. We are thankful for the continued support from passionate investors who have made it possible for us to revolutionize the way that CAD is diagnosed,” said Don Crawford, CEO of Analytics 4 Life. “Securing this oversubscribed financing fuels our rapid growth to advance development of our diagnostic tool and gives us the resources we need to deliver this game-changing technology to patients and physicians.”

Current diagnostic methods for CAD are costly, risky, and time-consuming. Analytics 4 Life seeks to address these challenges with its novel method of cardiac imaging. The Company’s state-of-the-art technology represents a new approach to cardiac imaging based on advanced disciplines of mathematics and physics combined with the power of cloud computing and artificial intelligence. The first application of this technology is CorVista™, a non-invasive, physician-directed diagnostic test that aims to identify the presence of CAD without radiation or cardiac stress.
CorVista is designed to scan signals naturally emitted by the body with a synchronous array of seven sensors on Analytics 4 Life’s proprietary collection device. After the signals are acquired, the signal package is instantaneously transmitted to the cloud where it is analyzed by a machine-learned algorithm to generate a unique image and a heart model indicating areas of potential heart disease associated with the presence of CAD. The results of the test are displayed on a secure physician web portal that, in combination with a patient’s medical history, risk factors, and symptoms, are used by the interpreting physician to recommend further treatment.

Coronary Artery Disease Learning and Algorithm Development (CADLAD) Clinical Study

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