50 citations · 57 across the 4 of their papers we have counts for
4 papers
A generalized framework to predict continuous scores from medical ordinal labels
Katharina V. Hoebel, Andreanne Lemay, John Peter Campbell +7
Many variables of interest in clinical medicine, like disease severity, are recorded using discrete ordinal categories such as normal/mild/moderate/severe. These labels are used to…
Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations
Aaron S. Coyner, Praveer Singh, James M. Brown +5
Background: Artificial intelligence (AI) may demonstrate racial bias when skin or choroidal pigmentation is present in medical images. Recent studies have shown that convolutional…
Accelerated Experimental Design for Pairwise Comparisons
Yuan Guo, Jennifer Dy, Deniz Erdogmus +5
Pairwise comparison labels are more informative and less variable than class labels, but generating them poses a challenge: their number grows quadratically in the dataset size. We…
High-resolution medical image synthesis using progressively grown generative adversarial networks
Andrew Beers, James Brown, Ken Chang +4
Generative adversarial networks (GANs) are a class of unsupervised machine learning algorithms that can produce realistic images from randomly-sampled vectors in a multi-dimensiona…