Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks

2 Mar 2020Chirag NagpalXinyu LiArtur Dubrawski

We describe a new approach to estimating relative risks in time-to-event prediction problems with censored data in a fully parametric manner. Our approach does not require making strong assumptions of constant baseline hazard of the underlying survival distribution, as required by the Cox-proportional hazard model... (read more)

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