These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
2. An Efficient Feature Selection Strategy Based on Multiple Support Vector Machine Technology with Gene Expression Data. Zhang Y; Deng Q; Liang W; Zou X Biomed Res Int; 2018; 2018():7538204. PubMed ID: 30228989 [TBL] [Abstract][Full Text] [Related]
3. Optimizing Texture Retrieving Model for Multimodal MR Image-Based Support Vector Machine for Classifying Glioma. Yang Y; Yan LF; Zhang X; Nan HY; Hu YC; Han Y; Zhang J; Liu ZC; Sun YZ; Tian Q; Yu Y; Sun Q; Wang SY; Zhang X; Wang W; Cui GB J Magn Reson Imaging; 2019 May; 49(5):1263-1274. PubMed ID: 30623514 [TBL] [Abstract][Full Text] [Related]
4. Computer-assisted lip diagnosis on Traditional Chinese Medicine using multi-class support vector machines. Li F; Zhao C; Xia Z; Wang Y; Zhou X; Li GZ BMC Complement Altern Med; 2012 Aug; 12():127. PubMed ID: 22898352 [TBL] [Abstract][Full Text] [Related]
5. Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics. Lin X; Li C; Zhang Y; Su B; Fan M; Wei H Molecules; 2017 Dec; 23(1):. PubMed ID: 29278382 [TBL] [Abstract][Full Text] [Related]
6. Ensemble Feature Learning of Genomic Data Using Support Vector Machine. Anaissi A; Goyal M; Catchpoole DR; Braytee A; Kennedy PJ PLoS One; 2016; 11(6):e0157330. PubMed ID: 27304923 [TBL] [Abstract][Full Text] [Related]
7. Radiomics assessment of bladder cancer grade using texture features from diffusion-weighted imaging. Zhang X; Xu X; Tian Q; Li B; Wu Y; Yang Z; Liang Z; Liu Y; Cui G; Lu H J Magn Reson Imaging; 2017 Nov; 46(5):1281-1288. PubMed ID: 28199039 [TBL] [Abstract][Full Text] [Related]
8. Tuning to optimize SVM approach for assisting ovarian cancer diagnosis with photoacoustic imaging. Wang R; Li R; Lei Y; Zhu Q Biomed Mater Eng; 2015; 26 Suppl 1():S975-81. PubMed ID: 26406101 [TBL] [Abstract][Full Text] [Related]
9. AdaBoost-based multiple SVM-RFE for classification of mammograms in DDSM. Yoon S; Kim S BMC Med Inform Decis Mak; 2009 Nov; 9 Suppl 1(Suppl 1):S1. PubMed ID: 19891795 [TBL] [Abstract][Full Text] [Related]
10. Imaging biomarker analysis of advanced multiparametric MRI for glioma grading. Vamvakas A; Williams SC; Theodorou K; Kapsalaki E; Fountas K; Kappas C; Vassiou K; Tsougos I Phys Med; 2019 Apr; 60():188-198. PubMed ID: 30910431 [TBL] [Abstract][Full Text] [Related]
11. Differential Diagnosis of Prostate Cancer Grade to Augment Clinical Diagnosis Based on Classifier Models with Tuned Hyperparameters. Alanezi ST; Kraśny MJ; Kleefeld C; Colgan N Cancers (Basel); 2024 Jun; 16(11):. PubMed ID: 38893281 [TBL] [Abstract][Full Text] [Related]
12. Recursive Support Vector Machine Biomarker Selection for Alzheimer's Disease. Zhang F; Petersen M; Johnson L; Hall J; O'Bryant SE J Alzheimers Dis; 2021; 79(4):1691-1700. PubMed ID: 33492292 [TBL] [Abstract][Full Text] [Related]
13. Final Gleason score prediction using discriminant analysis and support vector machine based on preoperative multiparametric MR imaging of prostate cancer at 3T. Citak-Er F; Vural M; Acar O; Esen T; Onay A; Ozturk-Isik E Biomed Res Int; 2014; 2014():690787. PubMed ID: 25544944 [TBL] [Abstract][Full Text] [Related]
14. SVM-RFE based feature selection and Taguchi parameters optimization for multiclass SVM classifier. Huang ML; Hung YH; Lee WM; Li RK; Jiang BR ScientificWorldJournal; 2014; 2014():795624. PubMed ID: 25295306 [TBL] [Abstract][Full Text] [Related]
15. Recursive cluster elimination (RCE) for classification and feature selection from gene expression data. Yousef M; Jung S; Showe LC; Showe MK BMC Bioinformatics; 2007 May; 8():144. PubMed ID: 17474999 [TBL] [Abstract][Full Text] [Related]
16. SVM-RFE: selection and visualization of the most relevant features through non-linear kernels. Sanz H; Valim C; Vegas E; Oller JM; Reverter F BMC Bioinformatics; 2018 Nov; 19(1):432. PubMed ID: 30453885 [TBL] [Abstract][Full Text] [Related]
17. MSVM-RFE: extensions of SVM-RFE for multiclass gene selection on DNA microarray data. Zhou X; Tuck DP Bioinformatics; 2007 May; 23(9):1106-14. PubMed ID: 17494773 [TBL] [Abstract][Full Text] [Related]
18. Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction. Shi P; Ray S; Zhu Q; Kon MA BMC Bioinformatics; 2011 Sep; 12():375. PubMed ID: 21939564 [TBL] [Abstract][Full Text] [Related]
19. An efficient alpha seeding method for optimized extreme learning machine-based feature selection algorithm. Ding X; Yang F; Jin S; Cao J Comput Biol Med; 2021 Jul; 134():104505. PubMed ID: 34102404 [TBL] [Abstract][Full Text] [Related]
20. 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] [Next] [New Search]