156
Participants
Start Date
February 22, 2018
Primary Completion Date
November 11, 2019
Study Completion Date
November 11, 2019
AS Algorithm 1
Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater aortic stenosis from controls having structurally normal hearts with no greater than mild valvular heart disease at any location.
AS Algorithm 2
Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater aortic stenosis from controls having any findings other than moderate-to-severe or greater aortic stenosis.
MR Algorithm 1
Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater mitral regurgitation from controls having structurally normal hearts with no greater than mild valvular heart disease at any location.
MR Algorithm 2
Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater mitral regurgitation from controls having any findings other than moderate-to-severe or greater mitral regurgitation.
University of California San Francisco, San Francisco
Collaborators (1)
Eko Devices, Inc.
INDUSTRY
University of California, San Francisco
OTHER