Genetic programming for classification and feature selection: analysis of 1H nuclear magnetic resonance spectra from human brain tumour biopsies

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{gray:1998:GPcfs:aNMRshbtb,
  author =       "Helen F. Gray and Ross J. Maxwell and 
                 Irene Martinez-Perez and Carles Arus and Sebastian Cerdan",
  title =        "Genetic programming for classification and feature
                 selection: analysis of {1H} nuclear magnetic resonance
                 spectra from human brain tumour biopsies",
  journal =      "NMR Biomedicine",
  year =         "1998",
  volume =       "11",
  number =       "4-5",
  pages =        "217--224",
  month =        jun # "-" # aug,
  keywords =     "genetic algorithms, genetic programming, brain tumour,
                 artificial intelligence, classification, feature
                 selection",
  ISSN =         "1099-1492",
  DOI =          "doi:10.1002/(SICI)1099-1492(199806/08)11:4/5<217::AID-NBM512>3.0.CO;2-4",
  size =         "8 pages",
  abstract =     "Genetic programming (GP) is used to classify tumours
                 based on 1H nuclear magnetic resonance (NMR) spectra of
                 biopsy extracts. Analysis of such data would ideally
                 give not only a classification result but also indicate
                 which parts of the spectra are driving the
                 classification (i.e. feature selection). Experiments on
                 a database of variables derived from 1H NMR spectra
                 from human brain tumour extracts (n = 75) are reported,
                 showing GP's classification abilities and comparing
                 them with that of a neural network. GP successfully
                 classified the data into meningioma and non-meningioma
                 classes. The advantage over the neural network method
                 was that it made use of simple combinations of a small
                 group of metabolites, in particular glutamine,
                 glutamate and alanine. This may help in the choice of
                 the most informative NMR spectroscopy methods for
                 future non-invasive studies in patients.",
  notes =        "PMID: 9719576, UI: 98384081 Computer Science
                 Department, Arhus University, Denmark.",
}

Genetic Programming entries for Helen Gray Ross James Maxwell Irene Martinez-Perez Carles Arus Sebastian Cerdan

Citations