Figure 10 : Overview of the process of training and testing of the deep learning classifiers for invasive breast cancer detection on whole-slide images.

From: Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

Figure 10

The training data set had 349 ER+ invasive breast cancer patients (HUP N = 239, UHCMC/CWRU N = 110). The validation data set contained 40 ER+ invasive breast cancer patients from the Cancer Institute of New Jersey (CINJ). The test data set was composed of 195 ER+ invasive breast cancer cases from TCGA and 21 negative controls (NC).