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A gene expression analysis system for medical diagnosis
Authors
D. Maroulis Iakovidis, D. Karkanis, S. Flaounas, I.
Publication date
1 January 2006
Publisher
Abstract
In this paper we present a novel system that utilizes molecular-level information for medical diagnosis. It accepts high dimensional vectors of gene expressions, quantified by means of microarray image analysis, as input. The proposed system incorporates various data pre-processing methods, such as missing values estimation and data normalization. A novel approach to the classification of gene expression vectors in multiple classes that embodies vari-ous gene selection methods has been adopted for diagnostic purposes. The pro-posed system has been extensively tested on various, publicly available data-sets. We demonstrate its performance for prostate cancer diagnosis and corn-pare its performance with a well established multiclass classification scheme. The results show that the proposed system could be proved a valuable diagnostic aid in medicine. © 2006 International Federation for Information Processing
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Last time updated on 10/02/2023