AI RESEARCH
FairLogue: A Toolkit for Intersectional Fairness Analysis in Clinical Machine Learning Models
arXiv CS.LG
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ArXi:2604.04858v1 Announce Type: new Objective: Algorithmic fairness is essential for equitable and trustworthy machine learning in healthcare. Most fairness tools emphasize single-axis graphic comparisons and may miss compounded disparities affecting intersectional populations. This study