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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Rogers, S., Girolami, M., Krebs, R., & Mischak, H. (2005). Disease classification from capillary electrophoresis: Mass spectrometry. In Lecture Notes in Computer Science (Vol. 3686, pp. 183–191). Springer Verlag. https://doi.org/10.1007/11551188_20
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