Figure 2.

Evaluation of the prediction performance for the biomarkers MSI, BRAF, and KRAS in single cohort and large-scale multi-centric experiments

Experimental results for MSI-high (A–C), BRAF (D,E), and KRAS (F,G) prediction. All values represent the mean of 5-fold cross-validation: (A) AUROC scores for single cohort experiments for all CRC cohorts ordered by size of the cohort. Each row shows the test performance of training on one cohort with the in-domain test results in the diagonal. Results for our transformer approach, AttentionMIL, and CNN approach (results taken from Echle et al.) are visualized separately. Note that compared to AttentionMIL and CNN, our transformer not only shows higher overall prediction accuracy but also better model generalizability, demonstrated by a smaller gap between internal and external testing cohorts. Raw data for the heatmap in Table S5.

(B) Receiver operator curve (ROC) for the model trained on all resection cohorts except YCR-BCIP, tested on YCR-BCIP.

(C) Precision recall curve (PRC) for the model trained on all resection cohorts except YCR-BCIP, tested on YCR-BCIP.

(D) AUROC scores for single cohort experiments.

(E) ROC for the model trained on all BRAF cohorts except Epi700, tested on Epi700.

(F) AUROC scores for single cohort experiments.

(G) ROC for the model trained on all KRAS cohorts except Epi700, tested on Epi700.