Rapid identification of Streptococcus and Enterococcus species using diffuse reflectance-absorbance Fourier transform infrared spectroscopy and artificial neural networks
Diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR) was used to analyse 19 hospital isolates which had been identified by conventional means to one of Enterococcus faecalis, E. faecium, Streptococcus bovis, S. mitis, S. pneumoniae, or S. pyogenes. Principal components anal...
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Published in | FEMS microbiology letters Vol. 140; no. 2; pp. 233 - 239 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.07.1996
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Subjects | |
Online Access | Get full text |
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Summary: | Diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR) was used to analyse 19 hospital isolates which had been identified by conventional means to one of
Enterococcus faecalis, E. faecium, Streptococcus bovis, S. mitis, S. pneumoniae, or
S. pyogenes. Principal components analysis of the FT-IR spectra showed that this ‘unsupervised’ learning method failed to form six separable clusters (one for each species) and thus could not be used to identify these bacteria based on their FT-IR spectra. By contrast, artificial neural networks (ANNs) could be trained by ‘supervised’ learning (using the back-propagation algorithm) with the principal components scores of derivatised spectra to recognise the strains from their FT-IR spectra. These results demonstrate that the combination of FT-IR and ANNs provides a rapid, novel and accurate bacterial identification technique. |
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ISSN: | 0378-1097 1574-6968 |
DOI: | 10.1016/0378-1097(96)00186-3 |