Us2.ai partners with leading academic medical center to collaborate on AI-enabled echocardiography software
Press releases may be edited for formatting or style | September 13, 2023
Artificial Intelligence
Cardiology
SINGAPORE--(BUSINESS WIRE)--Us2.ai, a Singapore-based MedTech firm, has partnered with Duke University to co-develop and commercialize AI tools for echocardiography, to enable earlier detection, improved diagnosis and more efficient management of heart disease.
In clinical practice, echocardiography is now firmly established as a central, affordable front-line tool for diagnosis and management of a range of cardiac conditions. These include the syndrome of heart failure with a reduced or preserved left ventricular ejection fraction, cardiomyopathy, ischemia, acute myocardial infarction, valvular heart disease and/or pulmonary hypertension etc.
Even at the most well-resourced setting, the process of acquiring, measuring, and analyzing the images is time-consuming and labor-intensive, making the routine echocardiography application unsustainable. Ground-breaking machine learning technology from Us2.ai utilises rigorously tested artificial intelligence (AI) algorithms to reduce the time to process and interpret echocardiograms from 30 minutes to under 2 minutes, with zero clicks, zero variability and with an accuracy comparable to expert clinicians1.
“The presence of AI in cardiology is growing by day, from risk score generation to screening to management. Advances in deep learning have made automated analysis of medical images possible,” said Dr. Manesh Patel, Chief of Cardiology and Co-Director of the Heart Center at Duke University Health System. “We look forward to continuing our pioneering efforts to bring AI-automation to our echo labs and clinics.”
Once an echocardiographer/sonographer acquires the necessary images for a study, the FDA and CE cleared Us2 software automatically performs a quality check while simultaneously classifying, annotating and analyzing all the heart chambers, using both 2D and Doppler views to create a full echo report with specific cardiac diagnoses.
“This partnership accelerates our mission to automate the fight against heart disease,” said Dr. Carolyn Lam, Professor at Duke-NUS Graduate Medical School and co-founder of Us2.ai. “At Us2.ai, we continue to expand our collaborative network worldwide to further test and refine our innovative technology in different clinical settings and health care systems. We are proud to partner with Duke University and strengthen our global ties in cardiovascular research which we hope ultimately will benefit patients worldwide.”
“Even among the best specialists and heart care centers, the interpretation of echo images is subject to inter-and intra-reader variability and human error. The possibility of negating this variability with technology is necessary and exciting as it holds incredible potentials beyond cardiology clinics,“ said Dr. Madhav Swaminathan, Professor of Anesthesiology at Duke University and past President of the American Society of Echocardiography.
In clinical practice, echocardiography is now firmly established as a central, affordable front-line tool for diagnosis and management of a range of cardiac conditions. These include the syndrome of heart failure with a reduced or preserved left ventricular ejection fraction, cardiomyopathy, ischemia, acute myocardial infarction, valvular heart disease and/or pulmonary hypertension etc.
Even at the most well-resourced setting, the process of acquiring, measuring, and analyzing the images is time-consuming and labor-intensive, making the routine echocardiography application unsustainable. Ground-breaking machine learning technology from Us2.ai utilises rigorously tested artificial intelligence (AI) algorithms to reduce the time to process and interpret echocardiograms from 30 minutes to under 2 minutes, with zero clicks, zero variability and with an accuracy comparable to expert clinicians1.
“The presence of AI in cardiology is growing by day, from risk score generation to screening to management. Advances in deep learning have made automated analysis of medical images possible,” said Dr. Manesh Patel, Chief of Cardiology and Co-Director of the Heart Center at Duke University Health System. “We look forward to continuing our pioneering efforts to bring AI-automation to our echo labs and clinics.”
Once an echocardiographer/sonographer acquires the necessary images for a study, the FDA and CE cleared Us2 software automatically performs a quality check while simultaneously classifying, annotating and analyzing all the heart chambers, using both 2D and Doppler views to create a full echo report with specific cardiac diagnoses.
“This partnership accelerates our mission to automate the fight against heart disease,” said Dr. Carolyn Lam, Professor at Duke-NUS Graduate Medical School and co-founder of Us2.ai. “At Us2.ai, we continue to expand our collaborative network worldwide to further test and refine our innovative technology in different clinical settings and health care systems. We are proud to partner with Duke University and strengthen our global ties in cardiovascular research which we hope ultimately will benefit patients worldwide.”
“Even among the best specialists and heart care centers, the interpretation of echo images is subject to inter-and intra-reader variability and human error. The possibility of negating this variability with technology is necessary and exciting as it holds incredible potentials beyond cardiology clinics,“ said Dr. Madhav Swaminathan, Professor of Anesthesiology at Duke University and past President of the American Society of Echocardiography.
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