Anssi Vanhala, Eero A Haapala, Arja Sääkslahti, Airi Hakkarainen, Anna Widlund, Pirjo Aunio
Associations between physical activity, motor skills, executive functions and early numeracy in preschoolers
European journal of sport science
recent times timetoevent data time failure death routinely collected alongside highthroughput covariates highdimensional bioinformatics data often challenge classical survival models either infeasible fit produce low prediction accuracy due overfitting address issue focus shifted towards introducing novel approaches feature selection survival prediction article propose new hybrid feature selection approach handles highdimensional bioinformatics datasets improved survival prediction study explores efficacy four distinct variable selection techniques lasso rsfvs scad coxboost context nonparametric biomedical survival prediction leveraging methods conducted comprehensive variable selection processes subsequently survival analysis modelsspecifically coxph rsf deephit nnwere employed construct predictive models based selected variables furthermore introduce novel approach wherein variables consistently selected majority aforementioned feature selection techniques considered innovative strategy referred proposed method aims enhance reliability robustness variable selection subsequently improving predictive performance survival analysis models evaluate effectiveness proposed method compare performance proposed approach existing lasso rsfvs scad coxboost techniques using various performance metrics including integrated brier score ibs concordance index cindex integrated absolute error iae numerous highdimensional survival datasets real data applications reveal proposed method outperforms competing methods terms survival prediction accuracy