most citedInterpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance

4 citations · 4 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CL2021★ 4 cited

Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance

Joshua R. Minot, Nicholas Cheney, Marc Maier +3

Medical systems in general, and patient treatment decisions and outcomes in particular, are affected by bias based on gender and other demographic elements. As language models are…