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Bayesian Optimization of 2D Echocardiography Segmentation
Bayesian Optimization (BO) is a well-studied hyperparameter tuning technique that is more efficient than grid search for high-cost, high-parameter machine learning problems.
Model Averaging and Augmented Inference for Stable Echocardiography Segmentation using 2D ConvNets
The automatic segmentation of heart substructures in 2D echocardiography images is a goal common to both clinicians and researchers.
Interpretable Neural Networks for Predicting Mortality Risk using Multi-modal Electronic Health Records
We present an interpretable neural network for predicting an important clinical outcome (1-year mortality) from multi-modal Electronic Health Record (EHR) data.
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