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Generation of patient specific cardiac chamber models using generative neural networks under a Bayesian framework for electroanatomical mapping
A probabilistic machine learning model trained on a library of CT/MRI scans of the heart can be used during electroanatomical mapping to generate a patient-specific 3D model of the chamber being mapped.
Pruning a neural network using Bayesian inference
Neural network pruning is a highly effective technique aimed at reducing the computational and memory demands of large neural networks.
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