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Fig. 3 | BMC Medical Research Methodology

Fig. 3

From: DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network

Fig. 3

Simulated Nonlinear Experimental Log-Risk Surfaces. Log-risk surfaces of the nonlinear test set with respect to patient’s covariates x0 and x1. a The calculated true log-risk h(x) (Eq. 9) for each patient. b The predicted log-risk surface of \(\hat {h}_{\beta }(x)\) from the linear CPH model parameterized on β. The linear CPH predicts a constant log-risk. c The output of DeepSurv \(\hat {h}_{\theta }(x)\) is the estimated log-risk function

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