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NIH Grant Funds Machine Learning Tool for Chronic Disease Detection

The nearly $3 million grant supports the development of a machine learning algorithm that intends to improve the detection of the chronic disease, pulmonary hypertension.

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By Sarai Rodriguez

- Digital health vendor Eko received a $2.7 million Small Business Innovation Research (SBIR) Direct Phase II grant from the National Institutes of Health (NIH), funding a machine learning algorithm that will improve chronic disease detection. 

Eko said the algorithm detects and stratifies pulmonary hypertension (PH) by using phonocardiogram (PCG) and electrocardiogram (ECG) data from Eko's smart stethoscopes. 

PH is a rare chronic disease occurring when the pressure in the blood vessels leading from the heart to the lungs is abnormally high.