Subpopulation-specific machine learning prognosis for underrepresented patients with double prioritized bias correction

Abstract

Afrose, Song et al. highlight deficiencies in the widely accepted one-machine-learning-model-fits-all approach. The authors develop a bias correction method that produces specialized machine learning-based prognostication models for underrepresented racial and age groups.