Pages that link to "Item:Q961312"

The following pages link to Survival prediction using gene expression data: a review and comparison (Q961312):

Displaying 29 items.

• Testing the prediction error difference between 2 predictors (Q90629) (← links)
• Sparse classification with paired covariates (Q127641) (← links)
• Enhancing the lasso approach for developing a survival prediction model based on gene expression data (Q308770) (← links)
• Editorial: Statistical genetics \& statistical genomics: where biology, epistemology, statistics, and computation collide (Q961300) (← links)
• A two-component Weibull mixture to model early and late mortality in a Bayesian framework (Q962272) (← links)
• An integrative pathway-based clinical-genomic model for cancer survival prediction (Q988098) (← links)
• Determining cutoff point of ensemble trees based on sample size in predicting clinical dose with DNA microarray data (Q2013966) (← links)
• An efficient algorithm for joint feature screening in ultrahigh-dimensional Cox's model (Q2032191) (← links)
• Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation (Q2103978) (← links)
• LCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data (Q2324979) (← links)
• A new variable selection approach using random forests (Q2361222) (← links)
• Sufficient dimension reduction on marginal regression for gaps of recurrent events (Q2443253) (← links)
• Survival analysis of microarray expression data by transformation models (Q2500272) (← links)
• High-dimensional Cox models: the choice of penalty as part of the model building process (Q2786152) (← links)
• \(L_{1}\) penalized estimation in the Cox proportional hazards model (Q2786153) (← links)
• The Dantzig Selector in Cox's Proportional Hazards Model (Q3103139) (← links)
• Microarray gene expression data with linked survival phenotypes: diffuse large-B-cell lymphoma revisited (Q3434144) (← links)
• Efficient approximate <i>k</i>‐fold and leave‐one‐out cross‐validation for ridge regression (Q4917509) (← links)
• Predicting Patient Survival from Proteomic Profile using Mass Spectrometry Data: An Empirical Study (Q4921574) (← links)
• An overview of techniques for linking high‐dimensional molecular data to time‐to‐event endpoints by risk prediction models (Q5391149) (← links)
• Assessment of evaluation criteria for survival prediction from genomic data (Q5391153) (← links)
• Doubly Penalized Buckley–James Method for Survival Data with High‐Dimensional Covariates (Q5450464) (← links)
• (Q5456730) (← links)
• Network-based survival analysis to discover target genes for developing cancer immunotherapies and predicting patient survival (Q5861604) (← links)
• (Q5886023) (← links)
• Identification of survival relevant genes with measurement error in gene expression incorporated (Q6115012) (← links)
• Bayesian ridge regression for survival data based on a vine copula-based prior (Q6120619) (← links)
• IDNetwork: a deep illness-death network based on multi-state event history process for disease prognostication (Q6628041) (← links)
• Penalized regression calibration: a method for the prediction of survival outcomes using complex longitudinal and high-dimensional data (Q6628325) (← links)