Technologies
This technology is a diagnostic tool combining electrocardiography with the power of deep learning algorithms to detect moderate to severe aortic stenosis, aortic regurgitation, and mitral regurgitation..
If left untreated, valvular heart disease can lead to serious complications including heart failure and death. Yet, most patients do not seek treatment until symptoms appear, which often occurs late in disease progression when interventions are less effective. As a result, many patients remain undiagnosed and fail to receive early interventional valve replacements. Currently, there are no cost-appropriate, population-wide screening practices to detect early signs of valvular heart disease, which may ultimately lead to better patient management and improved outcomes.
This technology uses deep learning analysis of the 12 lead electrocardiogram to accurately diagnoses aortic stenosis, aortic regurgitation, and mitral regurgitation. Rather than relying on patient presentation of symptoms and subsequent echocardiograms, this platform feeds low-cost electrocardiogram measurements to a trained deep learning algorithm which outputs patient diagnosis. Therefore, this technology offers an accessible solution to patient-wide screening, enabling earlier intervention and improved patient outcomes.
This technology was validated against echocardiography diagnosis in an independent, prospective multicenter study.
Patent Pending
IR CU21335
Licensing Contact: Joan Martinez