8 citations · 9 across the 2 of their papers we have counts for
4 papers
On the diminishing return of labeling clinical reports
Jean-Baptiste Lamare, Tobi Olatunji, Li Yao
Ample evidence suggests that better machine learning models may be steadily obtained by training on increasingly larger datasets on natural language processing (NLP) problems from…
Learning to estimate label uncertainty for automatic radiology report parsing
Tobi Olatunji, Li Yao
Bootstrapping labels from radiology reports has become the scalable alternative to provide inexpensive ground truth for medical imaging. Because of the domain specific nature, stat…
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…
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…