FairLogue shows that intersectional disparities in two clinical prediction tasks are largely consistent with randomized group membership.
Stigma, biomarkers, and algorithmic bias: recommendations for precision behavioral health with artificial intelligence
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FairLogue: Evaluating Intersectional Fairness across Clinical Machine Learning Use Cases using the All of Us Research Program
FairLogue shows that intersectional disparities in two clinical prediction tasks are largely consistent with randomized group membership.