Commentary on "Rapid identification of Streptococcus and Enterococcus species using diffuse reflectance-absorbance Fourier transform infrared spectroscopy and artificial neural networks"

FEMS Microbiol Lett. 2017 May 1;364(10):fnx018. doi: 10.1093/femsle/fnx018.


This is an invited review/commentary by the first and last authors of a paper that was the most cited in FEMS Microbiology Letters for 1996, presently showing in excess of 150 citations at Web of Science, and over 200 at Google Scholar. It was the first paper in which diffuse reflectance absorbance FT-IR spectroscopy was used with a supervised learning method in the form of artificial neural networks, and showed that this combination could succeed in discriminating a series of closely related, clinically relevant, Gram-positive bacterial strains.

Keywords: FT-IR spectroscopy; chemometrics; machine learning; neural networks.

Publication types

  • Comment

MeSH terms

  • Enterococcus*
  • Neural Networks, Computer
  • Spectroscopy, Fourier Transform Infrared
  • Streptococcus*