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Eko Murmur Analysis Software (EMAS)

Product
Developers: Eko
Date of the premiere of the system: July 2022
Branches: Pharmaceuticals, Medicine, Healthcare

2022: Smart Stethoscope Software Release

On July 12, 2022, a company Eko specializing in the development of digital medical technologies for the detection of diseases hearts and lungs announced the release software of Eko Murmur Analysis Software (EMAS) to identify and determine characteristic heart noises in adult and pediatric patients.

Eko's new generation of noise detection technologies allows the company to become the first and only manufacturer of smart stethoscopes on the market that can identify and distinguish between conventional and structural noises indicative of valvular heart disease.

Smart stethoscope released that detects heart noises

By combining artificial intelligence for noise analysis with its digital stethoscopes, Eko has turned a traditional stethoscope into an objective, low-cost and versatile screening tool that detects significant structural heart disease in seconds at the forefront of care.

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This recent FDA approval is another step toward Eko expanding access to improved heart health with clinically validated algorithms and best-in-class medical devices, said Connor Landgraf, co-founder and CEO of Eko. By making heart disease screening algorithms and digital stethoscopes available in viewing offices across the country, we are moving towards a future in which more objective and consistent screening of valvular heart disease can become the standard of care.
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The EMAS algorithm significantly improves the performance of healthcare professionals in the accurate and consistent detection of valgus heart disease, with an overall sensitivity of 85.6% and a specificity of 84.4%. Further analysis showed that among people aged 18 years and older, the EMAS algorithm detects structural noise with a sensitivity of 90.2% and a specificity of 90.6%. When using traditional stethoscopes to detect significant valvular heart disease, general practitioners (GPs) had a sensitivity of 44% and a specificity of 69%.[1]

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