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Journal Abstract Search

269 related items for PubMed ID: 17020063

  • 21. [An automated stellar spectra classification system based on non-parameter regression and nearest neighbor method].
    Zhang JN, Zhao YH, Liu R.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2009 Dec; 29(12):3424-8. PubMed ID: 20210186
    [Abstract] [Full Text] [Related]

  • 22. Mixture classification model based on clinical markers for breast cancer prognosis.
    Zeng T, Liu J.
    Artif Intell Med; 2010 Dec; 48(2-3):129-37. PubMed ID: 20005686
    [Abstract] [Full Text] [Related]

  • 23. Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure.
    Lewis DP, Jebara T, Noble WS.
    Bioinformatics; 2006 Nov 15; 22(22):2753-60. PubMed ID: 16966363
    [Abstract] [Full Text] [Related]

  • 24. A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach.
    Hua S, Sun Z.
    J Mol Biol; 2001 Apr 27; 308(2):397-407. PubMed ID: 11327775
    [Abstract] [Full Text] [Related]

  • 25. [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 27; 23(2):410-2. PubMed ID: 16706378
    [Abstract] [Full Text] [Related]

  • 26. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal.
    Asl BM, Setarehdan SK, Mohebbi M.
    Artif Intell Med; 2008 Sep 27; 44(1):51-64. PubMed ID: 18585905
    [Abstract] [Full Text] [Related]

  • 27. Support vector machine-based classification scheme for myoelectric control applied to upper limb.
    Oskoei MA, Hu H.
    IEEE Trans Biomed Eng; 2008 Aug 27; 55(8):1956-65. PubMed ID: 18632358
    [Abstract] [Full Text] [Related]

  • 28. Qualitative identification of tea categories by near infrared spectroscopy and support vector machine.
    Zhao J, Chen Q, Huang X, Fang CH.
    J Pharm Biomed Anal; 2006 Jun 16; 41(4):1198-204. PubMed ID: 16621404
    [Abstract] [Full Text] [Related]

  • 29. [Method of infrared spectrum on-line pattern recognition of mixed gas distribution based on SVM].
    Bai P, Ji JZ, Zhang FQ, Li Y, Liu JH, Zhu CC.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2008 Oct 16; 28(10):2278-81. PubMed ID: 19123388
    [Abstract] [Full Text] [Related]

  • 30. [Kernel regression application in estimating stellar fundamental parameters].
    Zhang JN, Wu FC, Luo AL.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2009 Apr 16; 29(4):1131-6. PubMed ID: 19626919
    [Abstract] [Full Text] [Related]

  • 31. Feasibility study on identification of green, black and Oolong teas using near-infrared reflectance spectroscopy based on support vector machine (SVM).
    Chen Q, Zhao J, Fang CH, Wang D.
    Spectrochim Acta A Mol Biomol Spectrosc; 2007 Mar 16; 66(3):568-74. PubMed ID: 16859975
    [Abstract] [Full Text] [Related]

  • 32. Classification of estrogen receptor-beta ligands on the basis of their binding affinities using support vector machine and linear discriminant analysis.
    Luan F, Liu HT, Ma WP, Fan BT.
    Eur J Med Chem; 2008 Jan 16; 43(1):43-52. PubMed ID: 17459530
    [Abstract] [Full Text] [Related]

  • 33. [Improving hyperspectral matching method through feature-selection/weighting based on SVM].
    Wang YY, Chen YH, Li J.
    Guang Pu Xue Yu Guang Pu Fen Xi; 2009 Mar 16; 29(3):735-9. PubMed ID: 19455811
    [Abstract] [Full Text] [Related]

  • 34. Improved recognition of sustained ventricular tachycardia from SAECG by support vector machine.
    Jankowski S, Szymanski Z, Piatkowska-Janko E, Oreziak A.
    Anadolu Kardiyol Derg; 2007 Jul 16; 7 Suppl 1():112-5. PubMed ID: 17584700
    [Abstract] [Full Text] [Related]

  • 35. Support vector machines and other pattern recognition approaches to the diagnosis of cerebral palsy gait.
    Kamruzzaman J, Begg RK.
    IEEE Trans Biomed Eng; 2006 Dec 16; 53(12 Pt 1):2479-90. PubMed ID: 17153205
    [Abstract] [Full Text] [Related]

  • 36. Classifying large chemical data sets: using a regularized potential function method.
    Mussa HY, Hawizy L, Nigsch F, Glen RC.
    J Chem Inf Model; 2011 Jan 24; 51(1):4-14. PubMed ID: 21155612
    [Abstract] [Full Text] [Related]

  • 37. 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 24; 41(2):161-75. PubMed ID: 17851055
    [Abstract] [Full Text] [Related]

  • 38. [Application of support vector machines to classification of blood cells].
    Wang H, Zheng C, Li Y, Zhu H, Yan X.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2003 Sep 24; 20(3):484-7. PubMed ID: 14565019
    [Abstract] [Full Text] [Related]

  • 39. A novel kernel-based maximum a posteriori classification method.
    Xu Z, Huang K, Zhu J, King I, Lyu MR.
    Neural Netw; 2009 Sep 24; 22(7):977-87. PubMed ID: 19167865
    [Abstract] [Full Text] [Related]

  • 40. Optimal feature selection for the assessment of vocal fold disorders.
    Khadivi Heris H, Seyed Aghazadeh B, Nikkhah-Bahrami M.
    Comput Biol Med; 2009 Oct 24; 39(10):860-8. PubMed ID: 19665112
    [Abstract] [Full Text] [Related]

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