Eko’s AI Analysis Algorithm Validated as a Clinical Tool for Detecting Heart Murmurs
The findings suggest utility of the FDA-cleared Eko AI algorithm as a frontline clinical tool to aid clinicians in screening for cardiac murmurs that may be caused by valvular heart disease.\nAlgorithm performance for detecting murmurs was found to have sensitivity of 90.0% and specificity of 91.4%, when excluding grade 1 murmurs which are difficult to hear.
- The findings suggest utility of the FDA-cleared Eko AI algorithm as a frontline clinical tool to aid clinicians in screening for cardiac murmurs that may be caused by valvular heart disease.\nAlgorithm performance for detecting murmurs was found to have sensitivity of 90.0% and specificity of 91.4%, when excluding grade 1 murmurs which are difficult to hear.
- The NIH-sponsored, multisite study published in the Journal of the American Heart Association was the largest study on AI analysis of cardiac murmurs.
- \xe2\x80\x9cIt takes expert clinicians many years to master the art of hearing and interpreting heart murmurs, and there is still a lot of variability.
- \xe2\x80\x9cNow for the first time, artificial intelligence is being applied to stethoscopic heart sounds to improve the auscultation skills of health care professionals.