Deep Clustering Survival Machines with Interpretable Expert Distributions

arXiv:2301.11826v4 Announce Type: replace
Abstract: Conventional survival analysis methods are typically ineffective to characterize heterogeneity in the population while such information can be used to assist predictive modeling. In this study, we propose a hybrid survival analysis method, referred to as deep clustering survival machines, that combines the discriminative and generative mechanisms. Similar to the mixture models, we assume that the timing information of survival data is generatively described by a mixture of certain numbers of parametric distributions, i.e., expert …

abstract analysis arxiv clustering cs.ai cs.lg expert generative hybrid information machines modeling population predictive predictive modeling study survival type