Catherine Feng

2 months ago | biorxiv.org | Catherine Feng |Fei Deng |Mary L. Disis |NAN GAO

AbstractClassification of patient multicategory survival outcomes is important for personalized cancer treatments. Machine Learning (ML) algorithms have increasingly been used to inform healthcare decisions, but these models are vulnerable to biases in data collection and algorithm creation. ML models have previously been shown to exhibit racial bias, but their fairness towards patients from different age and sex groups have yet to be studied.