Fig. 8: Ablation studies.

a averaged performance on pathological diagnosis (3 datasets), molecular prediction (12 datasets) and survival prediction (9 datasets), where ʻBeforeʼ refers to before pretraining, and ʻPʼ, ʻTʼ and ʻGʼ indicate pathology slides, pathology reports and gene data, respectively. Error bars represent standard errors across datasets for all bar plots. b visualization of feature space evolution: from before pretraining (initial) to Stage 1 (pretrained aggregator) and Stage 2 (mSTAR), where the areas in red bounding box are multiple tumor regions (1-7) of the case of patient_042_node_3 of CAMELYON17 dataset. Note that different tumor areas correspond to different spatial positions. c averaged performance (9 TCGA OS datasets) for ablating different pretraining objectives (Inter-modal Loss and Inter-cancer Loss) for survival prediction (Supplementary Table 4). d averaged performance (24 datasets) and resources comparisons between scaling slides only (Virchow) v.s. scaling modalities (mSTAR) for pretraining, with UNI as a baseline. Detailed performances of every dataset are presented in Supplementary Fig. 8 and detailed comparisons are showcased in Supplementary Table 5–6. Source data are provided as a Source Data file.