SENSORA™ Structural Murmur helps flag early signs of valvular heart disease through the detection of structural murmurs.
With over 1M heart sounds analyzed to date, our advanced machine learning algorithms are clinically validated at 90% sensitivity — double that of conventional practice.
2,3Our novel suite of algorithms goes beyond identification. It identifies and characterizes heart sounds, distinguishing if they’re systolic or diastolic, and innocent or structural.
A study published in JAHA (Journal of the American Heart Association) reveals that Eko's FDA-cleared algorithms, trained on over 15,000 heart sound recordings, outperform clinicians. In real clinical environments, they demonstrate a sensitivity of 97.9% and specificity of 90.6% when detecting clearly audible murmurs in adults.
2,3A study published in Circulation, an American Heart Association journal, demonstrated Eko's AI-enabled SENSORA™ Platform more than doubles valvular heart disease (VHD) detection sensitivity over traditional methods in primary care.
4Eko digital stethoscopes capture heart sounds and ECGs at the bedside, pairing with Eko software.
References
(1) Valvular Heart Disease, Centers for Disease Control and Prevention, 9 Dec. 2019, www.cdc.gov/heartdisease/valvular_disease.htm.
(2) Prince et al. Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease. Journal of American Heart Association, Vol.12 (2023): 20.
(3) Gardezi et al. Cardiac auscultation in diagnosing valvular heart disease: a comparison between general practitioners and cardiologists. European Heart Journal, Vol. 38 (2017): 11552.
(4) Rancier, M. A., Israel, I., Monickam, V., Prince, J., Verschoore, B., & Currie, C. (2023). Real World Evaluation of an Artificial Intelligence Enabled Digital Stethoscope for Detecting Undiagnosed Valvular Heart Disease in Primary Care. Circulation, 148, A13244.
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