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Proceedings Paper

Neural network analysis of chemical compounds in nonrebreathing Fisher-344 rat breath
Author(s): Robert E. Sackett; Steven K. Rogers; Martin P. DeSimio; James H. Raymer; Dennis W. Ruck; Matthew Kabrisky; Charles A. Bleckmann
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Paper Abstract

This research applies statistical and artificial neural network analysis to data obtained from measurement of organic compounds in the breath of Fisher-344 rats. The Research Triangle Institute (RTI) developed a breath collection system for use with rates in order to collect and measure volatile organic compounds (VOCs) exhaled. The RTI study tested the hypothesis that VOCs, including endogenous compounds, in breath can serve as markers to exposure to various chemicals such as drugs, pesticides, or carcinogens. A comparative analysis of chromatograms showed that the administration of carbon tetrachloride dramatically altered the VOCs measured in breath; both the compounds detected and their concentrations were greatly impacted. This research demonstrated that neural network analysis and classification discriminates between exposure to carbon tetrachloride versus no exposure. It also identified the chemical compounds in rat breath that best discriminate between carbon tetrachloride exposure and either a vehicle control or no dose. For the data set analyzed, 100 percent classification accuracy was achieved in classifying cases of exposure versus no exposure. The top three marker compounds were identified. The results obtained show that neural networks can be effectively used to analyze complex chromatographic data.

Paper Details

Date Published: 22 March 1996
PDF: 12 pages
Proc. SPIE 2760, Applications and Science of Artificial Neural Networks II, (22 March 1996); doi: 10.1117/12.235928
Show Author Affiliations
Robert E. Sackett, Air Force Institute of Technology (United States)
Steven K. Rogers, Air Force Institute of Technology (United States)
Martin P. DeSimio, Air Force Institute of Technology (United States)
James H. Raymer, Research Triangle Institute (United States)
Dennis W. Ruck, Air Force Institute of Technology (United States)
Matthew Kabrisky, Air Force Institute of Technology (United States)
Charles A. Bleckmann, Air Force Institute of Technology (United States)


Published in SPIE Proceedings Vol. 2760:
Applications and Science of Artificial Neural Networks II
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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