Eko Employs AI to Help in Detection of Aortic Stenosis

Eko, a digital health company is using artificial intelligence and machine learning to aid in the fight against heart disease. The Berkley, CA-based company recently unveiled its Aortic Stenosis (AS) detection algorithm at the American Society of Echocardiography (ASE) 2019 Scientific Sessions. The algorithm was developed and tested in partnership with the Northwestern Medicine Bluhm Cardiovascular Institute. It is significant and stands to be more objective application than current detection methods for AS. The disease is often initially identified during the physical exam when a provider hears a heart murmur using his or her stethoscope, though due to the subjectivity involved in using a stethoscope, combined with the difficult task of identifying subtle heart sounds like the AS murmur, it’s common for this to be missed in symptomatic patients, who are then sent home without follow-up. Early study results showed Eko's AI was able to accurately detect AS in a cohort of Aortic Stenosis patients with a sensitivity of 97.2% and a specificity of 86.4%. The Northwestern researchers concluded that assessment using Eko’s platform is a fast and effective method to screen for significant AS and should be validated in a primary care setting. The company said the algorithm represents a major step forward toward its mission to empower healthcare providers with tools to more accurately detect structural heart disease during primary care visits using th...
Source: MDDI - Category: Medical Devices Authors: Tags: Cardiovascular Source Type: news