SAN FRANCISCO – December 10, 2018 – Bay Labs, a medical technology company at the forefront of applying artificial intelligence (AI) to cardiovascular imaging, announced today a collaboration with Edwards Lifesciences focused on improving the detection of heart disease. The partnership involves multiple initiatives, including the development of new AI-powered algorithms in Bay Labs’ EchoMD measurement and interpretation software suite, the integration of EchoMD algorithms into Edwards Lifesciences’ CardioCare quality care navigation platform, and support for ongoing clinical studies at leading institutions.
Multiple EchoMD algorithms have been integrated into the CardioCare platform for investigational use to retrospectively analyze echocardiograms. The companies believe that incorporating these and future algorithms into clinical practice could help drive quality improvement and potentially increase accurate heart disease detection.
“Our vision is to improve patient care throughout the continuum from disease detection to appropriate intervention,” said Charles Cadieu, co-founder and CEO of Bay Labs. “Working with Edwards to deploy Bay Labs’ AI software with deep learning technology into clinical settings has the potential to derive quality improvements and to increase the accuracy of timely heart disease detection.”
“Improving detection of disease starts with better quality echoes,” said Dr. Madalina Petrescu, director of echocardiographic laboratory, Swedish Hospital. “CardioCare helps to reduce variability in echoes, and I believe Bay Labs’ AI technology has the potential to impact patient lives, namely by improving the accuracy of disease detection and diagnosis.”
The CardioCare program combines clinical consulting expertise with a cloud based platform to facilitate in the identification, referral, and care pathway management of patients with structural heart disease. CardioCare can help hospitals improve quality by reducing variability in echocardiography and ensure effective communication between care settings to ensure patients access to care. The EchoMD software suite assists cardiologists in automated review of images captured during echocardiograms.
● Bay Labs received FDA clearance for its first release of EchoMD in June 2018, which included AutoEF. AutoEF automates the calculation of left ventricular ejection fraction (EF), the single most widely used measurement of cardiac function.
● AutoEF relies on an Image Quality Score algorithm which quantifies the image quality of echo clips and enables display of the quality level alongside relevant images.
“It is unfortunate that patients suffering from severe aortic stenosis frequently do not receive a proper diagnosis, for a variety of reasons,” said Don Bobo, Edwards’ corporate vice president, strategy and corporate development. “The value of Bay Labs’ technology is in providing help for these patients to be appropriately diagnosed and successfully find their way to proper treatments.”
According to a 2014 publication from the American Heart Association, aortic valve stenosis is one of the most common valvular diseases and is the third most common cardiovascular disease in developed countries. Earlier detection of heart disease, using tools like echocardiography, may lead to more appropriate treatment for these patients.
About Bay Labs
Bay Labs is a San Francisco-based privately held company focused on increasing quality, value and access to medical imaging by combining deep learning and ultrasound. Founded in 2013, Bay Labs applies artificial intelligence to cardiovascular imaging, and its deep learning technology is designed to help medical professionals of all skill levels perform and interpret high-quality echocardiography to ultimately benefit their patients. Bay Labs is funded by Khosla Ventures, Data Collective, and other leading venture capital firms. For more information about Bay Labs, visit To learn more about Bay Labs and how AI-assisted acquisition and interpretation of echocardiograms could benefit medical practices and patients, visit www.baylabs.io/.
