Performance comparison of machine learning methods for prognosis of hormone receptor status in breast cancer tissue samples

Abstract

We examined the classification and prognostic scoring performances of several computer methods on different feature sets to obtain objective and reproducible analysis of estrogen receptor status in breast cancer tissue samples.