6 papers
Training-inference input alignment outweighs framework choice in longitudinal retinal image prediction
Liyin Chen, Nazlee Zebardast, Mengyu Wang +2
Predicting disease progression from longitudinal imaging is useful for clinical decision making and trial design. Recent methods have moved toward increasing generative complexity,…
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…
FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA
Minghan Li, Congcong Wen, Yu Tian +5
Fairness remains a critical concern in healthcare, where unequal access to services and treatment outcomes can adversely affect patient health. While Federated Learning (FL) presen…
Evaluation of In Vivo Subject-Specific Mechanical Modeling of the Optic Nerve Head for Robust Assessment of Ocular Mechanics
Soumaya Ouhsousou, Lucy Q. Shen, Chhavi Saini +3
To establish the tissue regions necessary to accurately represent the mechanics of the optic nerve head (ONH), imaging data of the ONH from 2 healthy subjects were used to create i…
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…
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…