Springer, Lecture Notes in Computer Science, p. 183-191, 2005
DOI: 10.1007/11551188_20
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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.