Can an automated deep learning pipeline accurately identify clinically significant tricuspid regurgitation in echocardiography?
An open-source automated deep learning pipeline demonstrates excellent performance in identifying clinically significant tricuspid regurgitation on echocardiography.
In this study, an automated pipeline was developed to identify clinically significant TR with excellent performance. With open-source code and weights, this project can serve as the foundation for future prospective evaluation of artificial intelligence-assisted workflows in echocardiography.
Vrudhula et al. (Wed,) studied this question.
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