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Compstat pp 148–153Cite as

Classification of Tumour 1H NMR Spectra using Nonlinear Approaches

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Abstract

Different linear and nonlinear techniques for the discrimination and classification of multivariate data sets were applied to a set of data from 231 urine samples of healthy volunteers and patients with various forms of cancer (four disease classes), inflammatory and infectious diseases.

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References

  • Breiman, L., Friedman, J.H., Olshen, R.A. and Stone, C.J. (1984).Classificalion and Regression Trees. Monterey: Wadsworth & Brooks/Cole.

    Google Scholar 

  • Breiman, L. and Ihaka, R. (1985). Nonlinear Discriminant Analysis via ACE and Scaling. Technical Report 40, U.C. Berkeley Statistics Department.

    Google Scholar 

  • Friedman, J. (1991). Multivariate adaptive regression splines (with discussion). Annals of Statistics, Vol. 19, 1–141.

    Article  Google Scholar 

  • Hastie, T.J. and Tibshirani, R.J. (1990). Generalized Additive Models. London: Chapman and Hall.

    Google Scholar 

  • Hastie, T.J., Tibshirani, R.J. and Buja, A. (1993). Flexible Discriminant Analysis by Optimal Scoring. Preprint.

    Google Scholar 

  • Reininghaus, F. (1992). NMR-spektroskopische Untersuchungen von Körperflissigkeiten: Studie zur Unterscheidung verschiedener Erkrankungen und Krebs mittels 1H-NMR-Spektroskopie menschlichen Urins. Dissertation, Universität Witten/Herdecke.

    Google Scholar 

  • Ripley, B. D. (1993). Statistical aspects of neural networks. In Chaos and Networks — Statistical and Probabilistic Aspects (eds O. E. Barndorff-Nielsen, D. R. Cox, J. L. Jensen and W. S. Kendall ), 40–123. London: Chapman and Hall.

    Chapter  Google Scholar 

  • Stone, M. (1974). Cross-validation choice and assessment of statistical predictions. Journal of the Royal Statistical Society, B, Vol. 36, 111–147.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Biostatistik, Deutsches Krebsforschungszentrum, Heidelberg, Germany

    Axel Benner

Authors
  1. Axel Benner
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Editor information

Editors and Affiliations

  1. Department for Statistics and Probability Theory, University of Technology Vienna, Wiedner Hauptstraße 8-10, A-1040, Vienna, Austria

    Rudolf Dutter

  2. Department of Statistics, OR and Computer Science, University Vienna, Universitätsstraße 5, A-1010, Vienna, Austria

    Wilfried Grossmann

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© 1994 Springer-Verlag Berlin Heidelberg

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Benner, A. (1994). Classification of Tumour 1H NMR Spectra using Nonlinear Approaches. In: Dutter, R., Grossmann, W. (eds) Compstat. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-52463-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-52463-9_14

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-0793-6

  • Online ISBN: 978-3-642-52463-9

  • eBook Packages: Springer Book Archive

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