Fig. 1

Proposed annotation-free deep learning framework for HER2 status classification from WSIs: a, Image segmentation divides images into distinct regions; b, Features are extracted from tissue regions of the WSI using image patches; c, Pre-computed feature vectors of image patches are input into the model. An attention network consolidates patch-level information into slide-level representations, which are utilized for the final diagnostic prediction; d, Strongly patched (red) and weakly patched (blue) regions serve as representative samples to guide clustering layers in distinguishing between positive and negative instances of distinct classes