AI-Driven Cardiac Ultrasound Company Bay Labs Announces Two Presentations At TCT2017

SAN FRANCISCO, Calif. – October 25, 2017 – Bay Labs, a medical technology company at the forefront of applying artificial intelligence to cardiovascular imaging, today announced that Emeritus Professor of Medicine (Cardiology) at Emory University School of Medicine and the company’s Chief Medical Officer Randolph P. Martin, M.D. FACC, FASE, has been invited to be a faculty member and present at the upcoming 29th Transcatheter Cardiovascular Therapeutics (TCT) annual scientific symposium of the Cardiovascular Research Foundation (CRF) meeting in Denver.  Dr. Martin’s two presentations will focus on how advances in artificial intelligence, machine learning, and deep learning can impact the role that cardiovascular imaging and echocardiography play in the diagnosis and management of heart diseases, especially those affecting the heart valves.

Attendees will have the opportunity to learn more about artificial intelligence and deep learning’s role in echocardiography and valvular heart diseases at the following presentations being made by Dr. Martin:

●        Using Artificial Intelligence (Machine Learning) to Direct Acquisition and Interpretation of Echocardiograms – Improving Access and Quality of Valve Disease Diagnosis: Monday, October 30, 4:04 PM, Colorado Convention Center, Mile High Ballroom 2B-3B.

●        Advances in Structural Heart Disease Imaging (Workflow Advances, Automated Quantification, and Machine Learning): Wednesday, November 1, 1:15 PM, Colorado Convention Center, Room 605.

Today, physicians seek consistent, high-quality imaging studies with quantitative assessments from imaging labs to the point of care.  Such studies aid in the timely and appropriate diagnosis and treatment of heart disease around the world.  Deep learning, a type of artificial intelligence algorithm, has great promise to aid in the acquisition and interpretation of echocardiographic exams (ultrasound images of the heart) and may improve the treatment of heart diseases.

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 being designed to help medical professionals of all skill levels perform and interpret high-quality echocardiography to ultimately benefit their patients.  Bay Labs products are for investigational use only and currently are not for sale.  For more information about Bay Labs, visit www.baylabs.io/.

About Randolph P. Martin
Randolph P. Martin, FACC, FASE, FESC, MD is one of the pioneers in the field of noninvasive cardiology, using ultrasound – echocardiography – to diagnose cardiovascular conditions.  He attended Emory University School of Medicine, graduating summa cum laude in 1969, and went on to hold faculty positions and clinical staff positions at Stanford University, the University of Virginia, the Mayo Medical School and Mayo Clinic, and Emory University, where he served as professor of medicine and director of noninvasive cardiology for 20 years.  He has over 195 publications to his credit in peer-reviewed journals and textbooks and serves or has served on editorial boards of some of the most prestigious cardiovascular journals.  Dr. Martin is the past president of the American Society of Echocardiography, an organization of 16,000 cardiovascular specialists and the second-largest group of cardiovascular specialists in North America.  Over his career, Dr. Martin has been a frequent invited lecturer at national and international cardiology conferences.  Additionally, for 15 years he was medical correspondent for WSBTV in Atlanta and was awarded the American Heart Association's Howard L. Lewis Lifetime Achievement Award for Medical Reporting.  He currently is the chief medical officer of Bay Labs and an emeritus professor of medicine (cardiology) at Emory University School of Medicine.

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