Without knowing the actual outcome, isn’t there also a possibility of error due to not knowing the race of the individual? They used mammogram images in the study and it is well known that incidence of breast cancer varies by race. Removing that information from the model could result in worse performance.
Well one thing you wouldn’t want to do is take the output of this model and then apply a correction factor for race on top of it, because the model is already taking that into account.
Well I suppose you only care about a correction factor to a binary model when it breaks a tie. You wouldn't want to apply a tiebreaker correction twice though.
