SurvBenchmark: comprehensive benchmarking study of survival analysis methods using both omics data and clinical data.

ABSTRACT: Survival analysis is a branch of statistics that deals with both the tracking of time and the survival status simultaneously as the dependent response. Current comparisons of survival model performance mostly center on clinical data with classic statistical survival models, with prediction accuracy often serving as the sole metric of model performance. Moreover, survival analysis approaches for censored omics data have not been thoroughly investigated. The common approach is to binarize the survival time and perform a classification analysis. Here, we develop a benchmarking design, SurvBenchmark, that evaluates a diverse collection of survival models for both clinical and omics data sets. SurvBenchmark not only focuses on classical approaches such as the Cox model but also evaluates state-

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC9338425 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature