no code implementations • 2 Apr 2019 • Li Yao, Jordan Prosky, Ben Covington, Kevin Lyman
This work provides a strong baseline for the problem of multi-source multi-target domain adaptation and generalization in medical imaging.
no code implementations • 1 Oct 2018 • Nithya Attaluri, Ahmed Nasir, Carolynne Powe, Harold Racz, Ben Covington, Li Yao, Jordan Prosky, Eric Poblenz, Tobi Olatunji, Kevin Lyman
Obtaining datasets labeled to facilitate model development is a challenge for most machine learning tasks.
no code implementations • 21 Mar 2018 • Li Yao, Jordan Prosky, Eric Poblenz, Ben Covington, Kevin Lyman
Diagnostic imaging often requires the simultaneous identification of a multitude of findings of varied size and appearance.
10 code implementations • ICLR 2018 • Li Yao, Eric Poblenz, Dmitry Dagunts, Ben Covington, Devon Bernard, Kevin Lyman
The field of medical diagnostics contains a wealth of challenges which closely resemble classical machine learning problems; practical constraints, however, complicate the translation of these endpoints naively into classical architectures.
1 code implementation • 25 Mar 2016 • Sasha Targ, Diogo Almeida, Kevin Lyman
Residual networks (ResNets) have recently achieved state-of-the-art on challenging computer vision tasks.