$$ \alpha $$ -KIDS: A Novel Feature Evaluation in the Ultrahigh-Dimensional Right-Censored Setting, With Application to Head and Neck Cancer.

ABSTRACT: Recent advances in sequencing technologies have allowed the collection of massive genome-wide information that substantially enhances the diagnosis and prognosis of head and neck cancer. Identifying predictive markers for survival time is crucial for devising prognostic systems and learning the underlying molecular drivers of the cancer course. In this paper, we introduce α$$ \alpha $$ -KIDS, a model-free feature screening procedure with false discovery rate (FDR) control for ultrahigh-dimensional right-censored data, which is robust against unknown censoring mechanisms. Specifically, our two-stage procedure initially selects a set of important features with a dual screening mechanism using nonparametric reproducing-kernel-based ANOVA statistics, followed by identifying a refined set of fe

SUBMITTER: Urmi AF 

PROVIDER: S-EPMC12261880 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature