Viz.ai Partners with Us2.ai to Deliver AI-Enabled Echocardiography Decision Support with the Viz™ Platform

Partnership delivers critical insights to cardiac care teams for faster patient triage and care

SAN FRANCISCO--(BUSINESS WIRE)--Viz.ai, the leader in AI-powered disease detection and intelligent care coordination, today announced it has partnered with Us2.ai, the developer of AI software that fully automates a complete echocardiography, or heart ultrasound, report. Under the partnership, Viz.ai will offer Us2.ai’s FDA-cleared and CE Marked echocardiogram viewing and measurement tools with the Viz™ Platform to improve and speed the coordination of care for patients with suspected heart disease, the leading cause of death worldwide.

“Echo is an essential tool in the delivery of cardiovascular care. We believe that no heart disease patient should have to wait for care when time is critical,” said Chris Mansi, CEO of Viz.ai. “The average time to complete an echo takes up to 60^[1] minutes, plus additional reporting time. Using AI can dramatically reduce this time burden, as well as ensure a uniform standard of excellence in reporting. We are proud to partner with Us2.ai to enhance and complement our comprehensive AI platform, tailoring it to cardiovascular needs, so that cardiologists and care teams can provide optimal care to more patients most efficiently.”

The partnership with Us2.ai expands Viz.ai’s leadership in the cardiovascular arena, where the company also has FDA-cleared AI modules for cryptogenic stroke, aortic disease, and pulmonary embolism with an automated right ventricle/left ventricle (RV/LV) ratio algorithm. Us2.ai’s technology is a patented, automated clinical workflow solution that recognizes and analyzes 2D and Doppler echo images for comprehensive cardiac measurements needed for the diagnosis, prediction and prognosis of heart disease and pulmonary hypertension. Us2.ai produces complete echo reports in less than 2 minutes.^[2] The Viz Platform with Us2.ai’s technology will help decrease the time from patient admission to treatment by expediting clinician access to echocardiogram reports and increasing patient access to time-critical diagnostics in the acute and post-acute care phases.

“Viz.ai is a natural partner for Us2.ai given the proven success of its care coordination platform and its vast network covering 200 million lives,” said Seth Koeppel, head of business development at Us2.ai. “With a national shortage of sonographers, the combination of our leading-edge applications will support hospitals and providers as well as patients. We look forward to bringing the power of our AI-enabled cardiovascular solution to more cardiac care teams and patients across the U.S.”

About Viz.ai, Inc.

Viz.ai is the pioneer in the use of AI algorithms and machine learning to increase the speed of diagnosis and care, covering more than 200 million lives across 1,200+ hospitals and health systems in the US and Europe. The AI-powered Viz Platform is a disease detection and intelligent care coordination solution that identifies more patients with a particular disease, informs critical decisions at the point of care, optimizes care pathways, and helps improve outcomes. Backed by clinical data, the Viz Platform delivers significant value to patients, providers, and pharmaceutical and medical device companies. For more information visit viz.ai.

About Us2.ai

Us2.ai uses machine learning to automate the fight against heart disease. The company’s software tools improve clinical decision making and cardiovascular research for clinical trials using echocardiography, the safest and most common cardiac imaging modality. Us2.ai connects institutions and imaging labs around the world on a platform of ready to use automation tools for view classification, segmentation and federated learning across diverse, anonymous patient and disease cohorts. Us2.ai is a fast-growing startup backed by IHH Healthcare, Heal Partners, Sequoia India and EDBI.

^[1] https://my.clevelandclinic.org/health/diagnostics/16947-echocardiogram#

^[2] Overall time may vary based on the interpreting physician and imaging source.