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Journal Abstract Search

286 related items for PubMed ID: 18701266

  • 1. An integrated scheme for feature selection and parameter setting in the support vector machine modeling and its application to the prediction of pharmacokinetic properties of drugs.
    Yang SY, Huang Q, Li LL, Ma CY, Zhang H, Bai R, Teng QZ, Xiang ML, Wei YQ.
    Artif Intell Med; 2009 Jun; 46(2):155-63. PubMed ID: 18701266
    [Abstract] [Full Text] [Related]

  • 2. In silico prediction of mitochondrial toxicity by using GA-CG-SVM approach.
    Zhang H, Chen QY, Xiang ML, Ma CY, Huang Q, Yang SY.
    Toxicol In Vitro; 2009 Feb; 23(1):134-40. PubMed ID: 18940245
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  • 3. Prediction models of human plasma protein binding rate and oral bioavailability derived by using GA-CG-SVM method.
    Ma CY, Yang SY, Zhang H, Xiang ML, Huang Q, Wei YQ.
    J Pharm Biomed Anal; 2008 Aug 05; 47(4-5):677-82. PubMed ID: 18455346
    [Abstract] [Full Text] [Related]

  • 4. Effect of molecular descriptor feature selection in support vector machine classification of pharmacokinetic and toxicological properties of chemical agents.
    Xue Y, Li ZR, Yap CW, Sun LZ, Chen X, Chen YZ.
    J Chem Inf Comput Sci; 2004 Aug 05; 44(5):1630-8. PubMed ID: 15446820
    [Abstract] [Full Text] [Related]

  • 5. ESVM: evolutionary support vector machine for automatic feature selection and classification of microarray data.
    Huang HL, Chang FL.
    Biosystems; 2007 Aug 05; 90(2):516-28. PubMed ID: 17280775
    [Abstract] [Full Text] [Related]

  • 6. Prediction of torsade-causing potential of drugs by support vector machine approach.
    Yap CW, Cai CZ, Xue Y, Chen YZ.
    Toxicol Sci; 2004 May 05; 79(1):170-7. PubMed ID: 14976348
    [Abstract] [Full Text] [Related]

  • 7. CARSVM: a class association rule-based classification framework and its application to gene expression data.
    Kianmehr K, Alhajj R.
    Artif Intell Med; 2008 Sep 05; 44(1):7-25. PubMed ID: 18586476
    [Abstract] [Full Text] [Related]

  • 8. 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 05; 41(2):161-75. PubMed ID: 17851055
    [Abstract] [Full Text] [Related]

  • 9. Prediction of chemical carcinogenicity by machine learning approaches.
    Tan NX, Rao HB, Li ZR, Li XY.
    SAR QSAR Environ Res; 2009 Oct 05; 20(1-2):27-75. PubMed ID: 19343583
    [Abstract] [Full Text] [Related]

  • 10. Prediction of P-glycoprotein substrates by a support vector machine approach.
    Xue Y, Yap CW, Sun LZ, Cao ZW, Wang JF, Chen YZ.
    J Chem Inf Comput Sci; 2004 Oct 05; 44(4):1497-505. PubMed ID: 15272858
    [Abstract] [Full Text] [Related]

  • 11. Application of irregular and unbalanced data to predict diabetic nephropathy using visualization and feature selection methods.
    Cho BH, Yu H, Kim KW, Kim TH, Kim IY, Kim SI.
    Artif Intell Med; 2008 Jan 05; 42(1):37-53. PubMed ID: 17997291
    [Abstract] [Full Text] [Related]

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