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Identification of Staphylococcus aureus infections in hospital environment: electronic nose based approach
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UNSPECIFIED (2005) Identification of Staphylococcus aureus infections in hospital environment: electronic nose based approach. SENSORS AND ACTUATORS B-CHEMICAL, 109 (2). pp. 355-362. doi:10.1016/j.snb.2005.01.013 ISSN 0925-4005.
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Official URL: http://dx.doi.org/10.1016/j.snb.2005.01.013
Abstract
An electronic nose (e-nose), the Cyrano Sciences' Cyranose 320 (C-320), comprising an array of 32 polymer carbon black composite sensors has been used to identify two species of Staphylococcus aureus bacteria, namely methicillin-resistant S. aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) responsible for ear nose and throat (ENT) infections when present in standard agar solution in the hospital environment. C-320 e-nose has also been used to identify coagulase-negative staphylococci (C-NS) in the hospital environment. Swab samples were collected from the infected areas of the ENT patients' ear, nose and throat regions. Gathered data were a very complex mixture of different chemical compounds. An innovative object-oriented data clustering approach was investigated for these groups of S. aureus data by combining the principal component analysis (PCA) based three-dimensional scatter plot, Fuzzy C Means (FCM) and self-organizing map (SOM) network. Using these three data clustering algorithms simultaneously better 'classification' of three bacteria subclasses were represented. Then three supervised classifiers, namely multi-layer perceptron (MLP), probabilistic neural network (PNN) and radial basis function network (RBF), were used to classify the three classes. A comparative evaluation of the classifiers was conducted for this application. The best results suggest that we are able to identify three bacteria subclasses with up to 99.69% accuracy with the application of the RBF network along with C-320. This type of bacteria data analysis and feature extraction is very difficult. But we can conclude that this preliminary study proves that e-nose based approach can provide very strong solution for identifying S. aureus infections in hospital environment and early detection. (C) 2005 Elsevier B.V. All rights reserved.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QD Chemistry | ||||
Journal or Publication Title: | SENSORS AND ACTUATORS B-CHEMICAL | ||||
Publisher: | ELSEVIER SCIENCE SA | ||||
ISSN: | 0925-4005 | ||||
Official Date: | 14 September 2005 | ||||
Dates: |
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Volume: | 109 | ||||
Number: | 2 | ||||
Number of Pages: | 8 | ||||
Page Range: | pp. 355-362 | ||||
DOI: | 10.1016/j.snb.2005.01.013 | ||||
Publication Status: | Published |
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