• DocumentCode
    394146
  • Title

    Diseases classification using support vector machine (SVM)

  • Author

    Sheng, Liu ; Qing, Song ; Wenjie, Hu ; Aize, Cao

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
  • Volume
    2
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    760
  • Abstract
    The paper proposed a new method: disease classification based on protein sequence. Support vector machine was used for this problem and a new encoding for the multicode protein sequence was suggested. Two extracted features were selected for classifying, the results showed the capability of SVM for such bioinformatics problems and the goodness of the system of protein sequence based disease classification. It gave error around 4-5%, which presented that although it is good for such problems, improvement of the algorithm also should be made.
  • Keywords
    biology computing; diseases; feature extraction; medical computing; proteins; support vector machines; SVM; bioinformatics problems; disease classification; multicode protein sequence; protein sequence; support vector machine; Bioinformatics; Biological information theory; Data mining; Diseases; Genomics; Machine learning; Protein sequence; Sequences; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1198160
  • Filename
    1198160