14 citations · 33 across the 5 of their papers we have counts for
5 papers
Automated Dynamic Bayesian Networks for Predicting Acute Kidney Injury Before Onset
David Gordon, Panayiotis Petousis, Anders O. Garlid +4
Several algorithms for learning the structure of dynamic Bayesian networks (DBNs) require an a priori ordering of variables, which influences the determined graph topology. However…
EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation
Bilwaj Gaonkar, Joel Beckett, Mark Attiah +8
Translation of fully automated deep learning based medical image segmentation technologies to clinical workflows face two main algorithmic challenges. The first, is the collection…
Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan?
Bilwaj Gaonkar, Matthew Edwards, Alex Bui +2
Yes, it can. Data augmentation is perhaps the oldest preprocessing step in computer vision literature. Almost every computer vision model trained on imaging data uses some form of…
An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification
Shiwen Shen, Simon X. Han, Denise R. Aberle +2
While deep learning methods are increasingly being applied to tasks such as computer-aided diagnosis, these models are difficult to interpret, do not incorporate prior domain knowl…
Aztec: A Platform to Render Biomedical Software Findable, Accessible, Interoperable, and Reusable
Wei Wang, Brian Bleakley, Chelsea Ju +9
Precision medicine and health requires the characterization and phenotyping of biological systems and patient datasets using a variety of data formats. This scenario mandates the c…