Skip to main content
Fig. 6 | BMC Cancer

Fig. 6

From: Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer

Fig. 6

Determining the optimal feature ranking method - ROC curves for different combinations of feature ranking methods (panels) and classification methods (lines) for separating low from high ODx patches. Top left: Ranksum (Wilcoxon rank sum). Top right: PCA-VIP. Bottom left: MRMR-MID. Bottom right: MRMR-MIQ. Each panel displays the ROC curve using either (solid) random forest, (dashed) neural network, (dotted) SVM, or (intermediate dash) LDA classification. Feature set includes stromal and epithelial features. AUC values for each curve are displayed in the legend

Back to article page