11 citations · 21 across the 4 of their papers we have counts for
5 papers
AI Fairness via Domain Adaptation
Neil Joshi, Phil Burlina
While deep learning (DL) approaches are reaching human-level performance for many tasks, including for diagnostics AI, the focus is now on challenges possibly affecting DL deployme…
TARA: Training and Representation Alteration for AI Fairness and Domain Generalization
William Paul, Armin Hadzic, Neil Joshi +2
We propose a novel method for enforcing AI fairness with respect to protected or sensitive factors. This method uses a dual strategy performing training and representation alterati…
AI Progress in Skin Lesion Analysis
Philippe M. Burlina, William Paul, Phil A. Mathew +3
We examine progress in the use of AI for detecting skin lesions, with particular emphasis on the erythema migrans rash of acute Lyme disease, and other lesions, such as those from…
Addressing Artificial Intelligence Bias in Retinal Disease Diagnostics
Philippe Burlina, Neil Joshi, William Paul +2
This study evaluated generative methods to potentially mitigate AI bias when diagnosing diabetic retinopathy (DR) resulting from training data imbalance, or domain generalization w…
Deep Learning based Retinal OCT Segmentation
Mike Pekala, Neil Joshi, David E. Freund +3
Our objective is to evaluate the efficacy of methods that use deep learning (DL) for the automatic fine-grained segmentation of optical coherence tomography (OCT) images of the ret…