195 citations · 308 across the 5 of their papers we have counts for
5 papers
Caveats in Generating Medical Imaging Labels from Radiology Reports
Tobi Olatunji, Li Yao, Ben Covington +2
Acquiring high-quality annotations in medical imaging is usually a costly process. Automatic label extraction with natural language processing (NLP) has emerged as a promising work…
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…