Figure 3
From: Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models
Interpreting deep survival models with risk backpropagation. (A) Backpropagation was used to calculate the sensitivity of predicted risk to each input feature, generating feature risk scores for each feature and patient. (B) Feature risk scores can be analyzed to gain insights into the deep survival model. Risk scores can be used to evaluate the prognostic significance of individual features, or to identify gene sets or molecular pathways that are enriched with high-risk or low-risk features.
