In a research article published this month in the journal BMC Medical Imaging, Duke AI Health Faculty Council Member Ricardo Henao joins first author Conor Artman to describe a new approach for using deep learning models to detect clinically significant data in echocardiograms. Unlike commonly used but data-intensive segmentation models, the authors propose a “Scaled Gumbel Softmax” deep learning model that offers improvements over existing models while requiring fewer resources.
