Disease Classification from Capillary Electrophoresis: Mass Spectrometry

  • Simon Rogers
  • Mark Girolami
  • Ronald Krebs
  • Harald Mischak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3686)

Abstract

We investigate the possibility of using pattern recognition techniques to classify various disease types using data produced by a new form of rapid Mass Spectrometry. The data format has several advantages over other high-throughput technologies and as such could become a useful diagnostic tool. We investigate the binary and multi-class performances obtained using standard classifiers as the number of features is varied and conclude that there is potential in this technique and suggest research directions that would improve performance.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Simon Rogers
    • 1
  • Mark Girolami
    • 1
  • Ronald Krebs
    • 2
  • Harald Mischak
    • 2
  1. 1.Bioinformatics Research Centre, Department of Computing ScienceUniversity of GlasgowGlasgowUK
  2. 2.Mosaiques Diagnostics and Therapeutics AGHannoverGermany

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