Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data
Fig 3
A. Hidden node activation weighted by the corresponding Cox layer coefficients of the TCGA KIRC dataset. The columns represent individual patient scores, ordered by their Prognostic Index. The rows represent the node activations. B. t-SNE plot of the top 20 nodes (left) and t-SNE of differentially expressed genes between the two groups with low and high prognostic index, respecitively (right). C. Gene Set Enrichment Analysis: significantly enriched KEGG pathways of the top 20 hidden nodes (adjusted p-value < 0.05).