Assessing Cardiac Function from Ultrasound Videos Using Deep Learning Algorithms

Stanford researchers have developed an algorithm using deep learning architectures to predict cardiac function (ejection fraction) and trace the endocardium of the left ventricle from ultrasound echocardiogram videos. Current methods rely on human interpretation of ultrasound videos, leading to assessment variability. This algorithm assesses cardiac function faster, more accurately, and reliably than humans.

Stage of Research