Figure 3.

Attention and class score visualization for better model interpretability

(A) Resection specimen from the external cohort YCR-BCIP. The three depicted slides are the same as in Echle et al.³ Tumor regions are outlined in black.

(B) Attention rollout per patch for our trained transformer-based feature aggregation model. Large values (yellow) signify a high contribution to the model’s prediction, small values (purple) a low contribution.

(C) MSI classification scores per patch, where MSI-high is the positive class and MS-stable is the negative class.

(D) The attention heatmaps from eight heads, four of the first and four of the second layer. The model weights are taken from the best-performing fold of the multi-centric training on all cohorts except YCR-BCIP.