Addressing Artificial Intelligence Bias in Retinal Disease Diagnostics

no code implementations • 28 Apr 2020 • Philippe Burlina, Neil Joshi, William Paul, Katia D. Pacheco, Neil M. Bressler

Using novel generative methods for addressing missing subpopulation training data (DR-referable darker-skin) achieved instead accuracy, for lighter-skin, of 72. 0% (65. 8%, 78. 2%), and for darker-skin, of 71. 5% (65. 2%, 77. 8%), demonstrating closer parity (delta=0. 5%) in accuracy across subpopulations (Welch t-test t=0. 111, P=. 912).

Domain Generalization