Latent diffusion models for survival analysis

TL;DR

This paper introduces Bayesian hierarchical models for survival analysis using diffusion processes to model hazard rates, and demonstrates efficient inference via Markov chain Monte Carlo methods.

Contribution

It presents a novel approach combining diffusion processes with Bayesian hierarchical models for survival analysis, along with efficient MCMC inference techniques.

Findings

Effective modeling of survival times with diffusion-based hazard rates

Efficient Bayesian inference via MCMC techniques

Potential improvements in survival analysis accuracy

Abstract

We consider Bayesian hierarchical models for survival analysis, where the survival times are modeled through an underlying diffusion process which determines the hazard rate. We show how these models can be efficiently treated by means of Markov chain Monte Carlo techniques.