Figure 1.

The MultiSurv model architecture. Input data are all from the NCI Genomic Data Commons database, including up to six different data modalities. Each data modality is handled by a dedicated DL submodel, trained to generate modality-specific feature representations. A data fusion layer combines the generated feature representation vectors into a single fused representation. A final neural network takes the fused feature representation and outputs a conditional survival probability for each of a set of pre-defined follow-up time intervals. Taking the cumulative product of the set of conditional survival probabilities produces the predicted survival curve. CNN convolutional neural network, FC fully-connected neural network.