1324 related articles for article (PubMed ID: 17851055)
1. A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.
Chen Z; Li J; Wei L
Artif Intell Med; 2007 Oct; 41(2):161-75. PubMed ID: 17851055
[TBL] [Abstract][Full Text] [Related]
2. CARSVM: a class association rule-based classification framework and its application to gene expression data.
Kianmehr K; Alhajj R
Artif Intell Med; 2008 Sep; 44(1):7-25. PubMed ID: 18586476
[TBL] [Abstract][Full Text] [Related]
3. Improving gene expression cancer molecular pattern discovery using nonnegative principal component analysis.
Han X
Genome Inform; 2008; 21():200-11. PubMed ID: 19425159
[TBL] [Abstract][Full Text] [Related]
4. Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE.
Niijima S; Kuhara S
BMC Bioinformatics; 2006 Dec; 7():543. PubMed ID: 17187691
[TBL] [Abstract][Full Text] [Related]
5. Mixture classification model based on clinical markers for breast cancer prognosis.
Zeng T; Liu J
Artif Intell Med; 2010; 48(2-3):129-37. PubMed ID: 20005686
[TBL] [Abstract][Full Text] [Related]
6. Predictive neural networks for gene expression data analysis.
Tan AH; Pan H
Neural Netw; 2005 Apr; 18(3):297-306. PubMed ID: 15896577
[TBL] [Abstract][Full Text] [Related]
7. Tumor classification ranking from microarray data.
Hewett R; Kijsanayothin P
BMC Genomics; 2008 Sep; 9 Suppl 2(Suppl 2):S21. PubMed ID: 18831787
[TBL] [Abstract][Full Text] [Related]
8. Incremental forward feature selection with application to microarray gene expression data.
Lee YJ; Chang CC; Chao CH
J Biopharm Stat; 2008; 18(5):827-40. PubMed ID: 18781519
[TBL] [Abstract][Full Text] [Related]
9. ESVM: evolutionary support vector machine for automatic feature selection and classification of microarray data.
Huang HL; Chang FL
Biosystems; 2007; 90(2):516-28. PubMed ID: 17280775
[TBL] [Abstract][Full Text] [Related]
10. Gene selection from microarray data for cancer classification--a machine learning approach.
Wang Y; Tetko IV; Hall MA; Frank E; Facius A; Mayer KF; Mewes HW
Comput Biol Chem; 2005 Feb; 29(1):37-46. PubMed ID: 15680584
[TBL] [Abstract][Full Text] [Related]
11. SVM-RFE with MRMR filter for gene selection.
Mundra PA; Rajapakse JC
IEEE Trans Nanobioscience; 2010 Mar; 9(1):31-7. PubMed ID: 19884101
[TBL] [Abstract][Full Text] [Related]
12. An efficient statistical feature selection approach for classification of gene expression data.
Chandra B; Gupta M
J Biomed Inform; 2011 Aug; 44(4):529-35. PubMed ID: 21241823
[TBL] [Abstract][Full Text] [Related]
13. Low rank updated LS-SVM classifiers for fast variable selection.
Ojeda F; Suykens JA; De Moor B
Neural Netw; 2008; 21(2-3):437-49. PubMed ID: 18343309
[TBL] [Abstract][Full Text] [Related]
14. New variable selection method using interval segmentation purity with application to blockwise kernel transform support vector machine classification of high-dimensional microarray data.
Tang LJ; Du W; Fu HY; Jiang JH; Wu HL; Shen GL; Yu RQ
J Chem Inf Model; 2009 Aug; 49(8):2002-9. PubMed ID: 19645418
[TBL] [Abstract][Full Text] [Related]
15. [Rule induction algorithm for brain glioma using support vector machine].
Li G; Yang J; Wang J; Geng D
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2006 Apr; 23(2):410-2. PubMed ID: 16706378
[TBL] [Abstract][Full Text] [Related]
16. Recursive fuzzy granulation for gene subsets extraction and cancer classification.
Tang Y; Zhang YQ; Huang Z; Hu X; Zhao Y
IEEE Trans Inf Technol Biomed; 2008 Nov; 12(6):723-30. PubMed ID: 19000951
[TBL] [Abstract][Full Text] [Related]
17. Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates.
Anand A; Suganthan PN
J Theor Biol; 2009 Aug; 259(3):533-40. PubMed ID: 19406131
[TBL] [Abstract][Full Text] [Related]
18. A novel feature selection approach for biomedical data classification.
Peng Y; Wu Z; Jiang J
J Biomed Inform; 2010 Feb; 43(1):15-23. PubMed ID: 19647098
[TBL] [Abstract][Full Text] [Related]
19. Hybrid huberized support vector machines for microarray classification and gene selection.
Wang L; Zhu J; Zou H
Bioinformatics; 2008 Feb; 24(3):412-9. PubMed ID: 18175770
[TBL] [Abstract][Full Text] [Related]
20. Gene selection and classification from microarray data using kernel machine.
Cho JH; Lee D; Park JH; Lee IB
FEBS Lett; 2004 Jul; 571(1-3):93-8. PubMed ID: 15280023
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
