Figure 4: Quantitative performance, local model explanation, and global interpretability analyses of PORPOISE in papillary renal cell carcinoma (KIRP).
A. For KIRP (n=253), low-risk cases (top, n=36) often have high attention paid to complex and curving papillary architecture while for high-risk cases (bottom, n=63), high attention is paid to denser areas of tumor cells. B. Local gene attributions for the corresponding low-risk (top) and high-risk (bottom) cases. C. Kaplan–Meier curves for omics-only (left, “SNN”), histology-only (center, “AMIL”) and multimodal fusion (right, “MMF”), showing improved separation using MMF. D. Global gene attributions across patient cohorts according to unimodal interpretability (left, “SNN”), and multimodal interpretability (right, “MMF”). SNN and MMF were both able to identify prognostic markers such as BAP1 in KIRP. MMF additionally attributes to other immune-related / prognostic genes such as PROCR and RIOK1 in KIRP. E. Exemplar high attention patches from low-risk (top) and high-risk (bottom) cases with corresponding cell labels. F. Quantification of cell types in high attention patches for each disease overall, showing increased epithelial cell and TIL presence.