GTC Silicon Valley-2019: Deep Learning Framework for Diagnostics and Patient-Specific Design of Bioprosthetic Heart Valves
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GTC Silicon Valley-2019 ID:S9455:Deep Learning Framework for Diagnostics and Patient-Specific Design of Bioprosthetic Heart Valves
Aditya Balu(Iowa State University),Adarsh Krishnamurthy(Iowa State University)
We'll present a deep learning-based analysis framework for making key decisions about heart valve replacement and valve design. We'll describe how we use deep learning to predict valve performance measures, which makes these measurements accessible to physicians who lack expert computational knowledge. We will explain how our trained DL framework can be used interactively to predict valve-performance measures with the same fidelity as time-consuming biomechanics simulations. We'll also discuss how our tool can help doctors with heart valve diagnosis, ultimately improving patient care.