Classification and feature selection applied to breast cancer diagnosis

  • Authors:

  • Olvi Managasarian

  • Affiliations:

  • University of Wisconsin, Madison, WI

  • Venue:
  • ACM SIGBIO Newsletter - Special issue on biomedical applications of knowledge discovery in databases
  • Year:
  • 1998

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Abstract

Mathematical programming techniques are applied to the problems of classification, feature selection and clustering. The resulting classification and feature selection algorithms have been applied to the problem of breast cancer diagnosis. The clustering algorithms have been applied to the problem of grouping breast cancer patients with similar prognosis, as determined by survival curves (Kaplan-Meier).