Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.
Young J JuhnEuijung RyuChung-Il WiKatherine S KingMomin M MalikSantiago Romero-BrufauChunhua WengSunghwan SohnRichard R SharpJohn D HalamkaPublished in: Journal of the American Medical Informatics Association : JAMIA (2022)
The HOUSES index allows AI researchers to assess bias in predictive model performance by SES. Although our case study was based on a small sample size and a single-site study, the study results highlight a potential strategy for identifying bias by using an innovative SES measure.