Bayesian Survival Analysis by Approximate Inference of Neural Networks

arXiv:2404.06421v1 Announce Type: new
Abstract: Predicting future events always comes with uncertainty, but traditional non-Bayesian methods cannot distinguish certain from uncertain predictions or explain the confidence in their predictions. In survival analysis, Bayesian methods applied to state-of-the-art solutions in the healthcare and biomedical field are still novel, and their implications have not been fully evaluated. In this paper, we study the benefits of modeling uncertainty in deep neural networks for survival analysis with a focus on prediction and calibration performance. …

abstract analysis approximate inference art arxiv bayesian biomedical confidence cs.lg events future healthcare inference networks neural networks novel predictions solutions state survival type uncertain uncertainty