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Pattern Recognition and Data Mining

Volume 3686 of the series Lecture Notes in Computer Science pp 183-191

Disease Classification from Capillary Electrophoresis: Mass Spectrometry

  • Simon RogersAffiliated withBioinformatics Research Centre, Department of Computing Science, University of Glasgow
  • , Mark GirolamiAffiliated withBioinformatics Research Centre, Department of Computing Science, University of Glasgow
  • , Ronald KrebsAffiliated withMosaiques Diagnostics and Therapeutics AG
  • , Harald MischakAffiliated withMosaiques Diagnostics and Therapeutics AG

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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.