657 citations · 957 across the 5 of their papers we have counts for
5 papers
A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging
Li Yao, Jordan Prosky, Ben Covington +1
This work provides a strong baseline for the problem of multi-source multi-target domain adaptation and generalization in medical imaging. Using a diverse collection of ten chest X…
Efficient and Accurate Abnormality Mining from Radiology Reports with Customized False Positive Reduction
Nithya Attaluri, Ahmed Nasir, Carolynne Powe +7
Obtaining datasets labeled to facilitate model development is a challenge for most machine learning tasks. The difficulty is heightened for medical imaging, where data itself is li…
Weakly Supervised Medical Diagnosis and Localization from Multiple Resolutions
Li Yao, Jordan Prosky, Eric Poblenz +2
Diagnostic imaging often requires the simultaneous identification of a multitude of findings of varied size and appearance. Beyond global indication of said findings, the predictio…
Learning to diagnose from scratch by exploiting dependencies among labels
Li Yao, Eric Poblenz, Dmitry Dagunts +3
The field of medical diagnostics contains a wealth of challenges which closely resemble classical machine learning problems; practical constraints, however, complicate the translat…
Resnet in Resnet: Generalizing Residual Architectures
Sasha Targ, Diogo Almeida, Kevin Lyman
Residual networks (ResNets) have recently achieved state-of-the-art on challenging computer vision tasks. We introduce Resnet in Resnet (RiR): a deep dual-stream architecture that…