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Clinical Chemistry 27: 580-585, 1981;
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Clinical Chemistry, Vol 27, 580-585, Copyright © 1981 by American Association for Clinical Chemistry

Metabolic abnormalities associated with diabetes mellitus, as investigated by gas chromatography and pattern-recognition analysis of profiles of volatile metabolites

G Rhodes, M Miller, ML McConnell and M Novotny

Patterns of volatile metabolites in urine, as obtained by glass- capillary gas chromatography, were investigated by use of a nonparametric pattern-recognition method, in an effort to detect abnormalities associated with diabetes. We used threshold logic unit analysis on a data set consisting of normal subjects and those with diabetes mellitus, and could predict patterns for volatile metabolites as belonging to the proper class in 94.83% of the cases examined. In addition, a feature-extraction algorithm isolated those volatile constituents that are most useful in making the normal/diabetic classification. We used gas chromatography/mass spectrometry to identify important profile constituents. Finally, these same pattern- recognition methods indicated strong sex-related patterns in these volatiles.


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P. Jurs
Pattern recognition used to investigate multivariate data in analytical chemistry
Science, June 6, 1986; 232(4755): 1219 - 1224.
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