Case Study

Automated Data Capture To Train An AI Algorithm With eSource

Source: Castor
Data Artificial Intelligence Algorithm iStock-1295900106

AusculThing’s AI algorithm is positioned to completely transform the way health care providers detect heart murmurs, enabling them with a far more precise tool than the human ear. Although, to train the algorithm to work more effectively, they would need to collect an enormous amount of data from over 1,700 patients across 5 sites.

Reinventing heart and lung sound readings:

Auscultation is traditionally a manual process, where a doctor, nurse or caregiver listens to the sounds of the body during a physical exam, and makes a recommendation or referral to a specialist based on what they hear. This process is highly subjective – what one provider hears may not be the same as another.  Also, conducting an accurate auscultation reading requires years of experience, a very trained ear, and an incredible amount of skill.  Inaccurate auscultation readings have the potential to completely overwhelm public healthcare systems, and even more critically, have dire consequences for patients that need specialty care.


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