Fig. 6: A selection of the histological features annotated by an expert pathologist.
From: Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides
The proportion of tiles annotated as containing a particular histological feature within clusters of tiles linked to high and low risk, as well as randomly selected ones, is presented alongside the significance of p values from the Chi-square test of independence computed between each group, adjusted for multiple testing using the Benjamini–Hochberg procedure. For each histological feature, the region of a WSI containing the annotated cluster of tiles is displayed, extracted both from the CANTO H&E dataset (upper histological image) and from the CANTO HES dataset (lower histological image). ns p > 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
