Logical analysis of survival data: prognostic survival models by detecting high-degree interactions in right-censored data

摘要

Motivation: Survival analysis involves predicting the time to event for patients in a dataset, based on a set of recorded attributes. In this study we focus on right-censored survival problems. Detecting high-degree interactions for the estimation of survival probability is a challenging problem in survival analysis from the statistical perspective.