41 citations · 162 across the 47 of their papers we have counts for
8 papers · 1 filter
On the Ramifications of Human Label Uncertainty
Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib
Humans exhibit disagreement during data labeling. We term this disagreement as human label uncertainty. In this work, we study the ramifications of human label uncertainty (HLU). O…
Clinical Contrastive Learning for Biomarker Detection
Kiran Kokilepersaud, Mohit Prabhushankar, Ghassan AlRegib
This paper presents a novel positive and negative set selection strategy for contrastive learning of medical images based on labels that can be extracted from clinical data. In the…
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics
Mohit Prabhushankar, Kiran Kokilepersaud, Yash-yee Logan +3
Clinical diagnosis of the eye is performed over multifarious data modalities including scalar clinical labels, vectorized biomarkers, two-dimensional fundus images, and three-dimen…
Introspective Learning : A Two-Stage Approach for Inference in Neural Networks
Mohit Prabhushankar, Ghassan AlRegib
In this paper, we advocate for two stages in a neural network's decision making process. The first is the existing feed-forward inference framework where patterns in given data are…
Gradient-Based Adversarial and Out-of-Distribution Detection
Jinsol Lee, Mohit Prabhushankar, Ghassan AlRegib
We propose to utilize gradients for detecting adversarial and out-of-distribution samples. We introduce confounding labels -- labels that differ from normal labels seen during trai…
DECAL: DEployable Clinical Active Learning
Yash-yee Logan, Mohit Prabhushankar, Ghassan AlRegib
Conventional machine learning systems that operate on natural images assume the presence of attributes within the images that lead to some decision. However, decisions in medical d…