Powerful Murmur Detection
SENSORA™ Structural Murmur helps flag early signs of valvular heart disease through the detection of structural murmurs.
The future of structural heart disease detection is here. Approximately 8 million Americans have valvular heart disease1 — a more well-known condition of structural disease. SENSORA™ Structural Murmur enables double the detection of structural heart murmurs2,3 in seconds, using a familiar clinical tool — the stethoscope.
Enhance the Physical Exam
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.
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A 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.
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SENSORA™ Structural Murmur Includes:
How SENSORA™ Structural Murmur Works:
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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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