Open access
Aug 2026
Reducing Racial Disparities in Stroke Thrombolysis Using Fairness-Aware Machine Learning.
A fairness-aware machine learning framework using counterfactual adjustment to account for historical inequities embedded in clinical data reduced treatment disparities by 64.8% without compromising predictive accuracy (AUC = 0.89).
J. Kabangu, V. Lopera, Teresia M. Perkins et al.
· Journal of Racial and Ethnic... · 0 citations