UNSPECIFIED. (2005) Data reduction in headspace analysis of blood and urine samples for robust bacterial identification. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 79 (3). pp. 259-271. ISSN 0169-2607

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Abstract

This paper demonstrates the application of chemical headspace analysis to the problem of classifying the presence of bacteria in biomedical samples by using computational tools. Blood and urine samples of disparate forms were analysed using a Cyrano Sciences C320 electronic nose together with an Agilent 4440 Chemosensor. The high dimensional data sets resulting from these devices present computational problems for parameter estimation of discriminant models. A variety. of data reduction and pattern recognition techniques were employed in an attempt to optimise the classification process. A 100% successful classification rate for the blood data from the Agilent 4440 was achieved by combining a Sammon mapping with a radia( basis function neural network. In comparison a successful classification rate of 80% was achieved for the urine data from the C320 which were analysed using a novel nonlinear time series model. (c) 2005 Elsevier Ireland Ltd. All rights reserved

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine
Journal or Publication Title:	COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Publisher:	ELSEVIER IRELAND LTD
ISSN:	0169-2607
Official Date:	September 2005
Volume:	79
Number:	3
Number of Pages:	13
Page Range:	pp. 259-271
Identification Number:	10.1016/j.cmpb.2005.04.003
Publication Status:	Published
URI:	http://wrap.warwick.ac.uk/id/eprint/6576

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