5 citations · 15 across the 14 of their papers we have counts for
5 papers · 1 filter
TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction
Leila Gheisi, Henry Chu, Raju Gottumukkala +4
The use of artificial intelligence (AI) in automated disease classification significantly reduces healthcare costs and improves the accessibility of services. However, this transfo…
On Demographic Group Fairness Guarantees in Deep Learning
Yan Luo, Congcong Wen, Min Shi +3
We present a theoretical framework analyzing the relationship between data distributions and fairness guarantees in equitable deep learning. We establish novel bounds that account…
FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian Perturbation
Yan Luo, Muhammad Osama Khan, Congcong Wen +6
Recent progress in generative AI, especially diffusion models, has demonstrated significant utility in text-to-image synthesis. Particularly in healthcare, these models offer immen…
FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classification
Yu Tian, Congcong Wen, Min Shi +6
Addressing fairness in artificial intelligence (AI), particularly in medical AI, is crucial for ensuring equitable healthcare outcomes. Recent efforts to enhance fairness have intr…
FairCLIP: Harnessing Fairness in Vision-Language Learning
Yan Luo, Min Shi, Muhammad Osama Khan +9
Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated i…