3 papers
cs.CY2026
Advancing Health Equity through Multi-Level Fairness in Health Informatics
Nick Souligne, Vignesh Subbian
The increasing integration of machine learning in healthcare has highlighted critical challenges related to fairness, transparency, and health equity. Specifically, the use of mult…
cs.LG2026
FairSelect: A Systematic Evaluation of Multi-Level and Intersectional Algorithmic Fairness
Nick Souligne, Isabella Mixton-Garcia, Vignesh Subbian
Algorithmic fairness methods are increasingly used to identify and mitigate bias in machine learning models, yet most approaches are evaluated in isolation and along single demogra…
cs.LG2026
FairLogue: A Toolkit for Intersectional Fairness Analysis in Clinical Machine Learning Models
Nick Souligne, Vignesh Subbian
Objective: Algorithmic fairness is essential for equitable and trustworthy machine learning in healthcare. Most fairness tools emphasize single-axis demographic comparisons and may…