ArticleApplied mathematics : a journal of Chinese universities2017
Feature selection of ultrahigh-dimensional covariates with survival outcomes: a selective review.
Article in Applied mathematics : a journal of Chinese universities, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Efficient Post-Shrinkage Estimation Strategies in High-Dimensional Cox's Proportional Hazards Models.Entropy (Basel, Switzerland) · 2025Article
- High-Dimensional Survival Analysis: Methods and Applications.Annual review of statistics and its application · 2023Article
- Gene Screening for Prognosis of Non-Muscle-Invasive Bladder Carcinoma under Competing Risks Endpoints.Cancers · 2023Article
- Article
- Forward regression for Cox models with high-dimensional covariates.Journal of multivariate analysis · 2019Article
- Quantile regression for survival data in modern cancer research: expanding statistical tools for precision medicine.Precision clinical medicine · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Many modern biomedical studies have yielded survival data with high-throughput predictors. The goals of scientific research often lie in identifying predictive biomarkers, understanding biological mechanisms and making accurate and precise predictions. Variable screening is a crucial first step in achieving these goals. This work conducts a selective review of feature screening procedures for survival data with ultrahigh dimensional covariates. We present the main methodologies, along with the key conditions that ensure sure screening properties. The practical utility of these methods is examined via extensive simulations. We conclude the review with some future opportunities in this field.
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Registered trials
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