BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

134 related articles for article (PubMed ID: 31692981)

  • 1. A Generic Sure Independence Screening Procedure.
    Pan W; Wang X; Xiao W; Zhu H
    J Am Stat Assoc; 2019; 114(526):928-937. PubMed ID: 31692981
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A generic model-free feature screening procedure for ultra-high dimensional data with categorical response.
    Cheng X; Wang H
    Comput Methods Programs Biomed; 2023 Feb; 229():107269. PubMed ID: 36463676
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Feature Screening via Distance Correlation Learning.
    Li R; Zhong W; Zhu L
    J Am Stat Assoc; 2012 Jul; 107(499):1129-1139. PubMed ID: 25249709
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models.
    Fan J; Feng Y; Song R
    J Am Stat Assoc; 2011 Jun; 106(494):544-557. PubMed ID: 22279246
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Nonparametric Independence Screening in Sparse Ultra-High Dimensional Varying Coefficient Models.
    Fan J; Ma Y; Dai W
    J Am Stat Assoc; 2014; 109(507):1270-1284. PubMed ID: 25309009
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A robust variable screening procedure for ultra-high dimensional data.
    Ghosh A; Thoresen M
    Stat Methods Med Res; 2021 Aug; 30(8):1816-1832. PubMed ID: 34053339
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The Kendall interaction filter for variable interaction screening in high dimensional classification problems.
    Anzarmou Y; Mkhadri A; Oualkacha K
    J Appl Stat; 2023; 50(7):1496-1514. PubMed ID: 37197752
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Feature Screening for High-Dimensional Variable Selection in Generalized Linear Models.
    Jiang J; Shang J
    Entropy (Basel); 2023 May; 25(6):. PubMed ID: 37372195
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Combined Performance of Screening and Variable Selection Methods in Ultra-High Dimensional Data in Predicting Time-To-Event Outcomes.
    Pi L; Halabi S
    Diagn Progn Res; 2018; 2():. PubMed ID: 30393771
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis.
    Cui H; Li R; Zhong W
    J Am Stat Assoc; 2015 Jun; 110(510):630-641. PubMed ID: 26392643
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening.
    Pan R; Wang H; Li R
    J Am Stat Assoc; 2016; 111(513):169-179. PubMed ID: 28127109
    [TBL] [Abstract][Full Text] [Related]  

  • 12. On correlation rank screening for ultra-high dimensional competing risks data.
    Chen X; Li C; Zhang T; Gao Z
    J Appl Stat; 2022; 49(7):1848-1864. PubMed ID: 35707564
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Feature Screening in Ultrahigh Dimensional Cox's Model.
    Yang G; Yu Y; Li R; Buu A
    Stat Sin; 2016; 26():881-901. PubMed ID: 27418749
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
    Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
    Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
    [TBL] [Abstract][Full Text] [Related]  

  • 15. PREDICTION OF TREATMENT OUTCOME FOR AUTISM FROM STRUCTURE OF THE BRAIN BASED ON SURE INDEPENDENCE SCREENING.
    Zhuang J; Dvornek NC; Zhao Q; Li X; Ventola P; Duncan JS
    Proc IEEE Int Symp Biomed Imaging; 2019 Apr; 2019():404-408. PubMed ID: 32256966
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Variable Selection for Sparse High-Dimensional Nonlinear Regression Models by Combining Nonnegative Garrote and Sure Independence Screening.
    Wu S; Xue H; Wu Y; Wu H
    Stat Sin; 2014 Jul; 24(3):1365-1387. PubMed ID: 25170239
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The Sparse MLE for Ultra-High-Dimensional Feature Screening.
    Xu C; Chen J
    J Am Stat Assoc; 2014; 109(507):1257-1269. PubMed ID: 25382886
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Censored Rank Independence Screening for High-dimensional Survival Data.
    Song R; Lu W; Ma S; Jeng XJ
    Biometrika; 2014; 101(4):799-814. PubMed ID: 25663709
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Variable Screening for Near Infrared (NIR) Spectroscopy Data Based on Ridge Partial Least Squares Regression.
    Zhao N; Xu Q; Tang ML; Wang H
    Comb Chem High Throughput Screen; 2020; 23(8):740-756. PubMed ID: 32342803
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Feature Selection for Varying Coefficient Models With Ultrahigh Dimensional Covariates.
    Liu J; Li R; Wu R
    J Am Stat Assoc; 2014 Jan; 109(505):266-274. PubMed ID: 24678135
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.