Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer - Nature Medicine

Arrow labels indicate each component’s output dimensions. Dim, mmhid, num_classes, etc. are defined model parameters. Fc represents a fully connected layer with the input dimension x and the output dimension y. Subblocks 1, … n-1 are structured identically to subblock 0.: Accuracy , AUPRC , AUROC , and F1-Score of the MSDLM and different classical machine learning techniques after training validation on the Mainz cohort. N = 11 models trained during 11-fold cross validation per group.

E, F: Precision-recall and receiver operator characteristics curves of the MSDLM and the classical machine learning techniques. The mean of the 11-fold cross validation is shown. Shaded area indicates 1 standard deviation . classifier).: Kaplan–Meier curves of the test cohort for each UICC stage stratified by AImmunoscore . N = 61 for UICC stage I, n = 128 for UICC stage II, n = 114 for UICC stage III, and n = 36 for UICC stage IV. Censors are indicated with a ‘+’. Log-rank test was used.

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