Colon cancer prediction with genetics profiles using evolutionary techniques

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@Article{Kulkarni20112752,
  author =       "Ashwinikumar Kulkarni and B. S. C. Naveen Kumar and 
                 Vadlamani Ravi and Upadhyayula Suryanarayana Murthy",
  title =        "Colon cancer prediction with genetics profiles using
                 evolutionary techniques",
  journal =      "Expert Systems with Applications",
  volume =       "38",
  number =       "3",
  pages =        "2752--2757",
  year =         "2011",
  ISSN =         "0957-4174",
  DOI =          "doi:10.1016/j.eswa.2010.08.065",
  URL =          "http://www.sciencedirect.com/science/article/B6V03-50YK82C-2/2/80df229bab9391914935d3f037d6b030",
  keywords =     "genetic algorithms, genetic programming, Microarray,
                 Gene expression, Tumour classification, t-Statistic,
                 Mutual information, Feature selection, Genetically
                 Evolved Decision Trees",
  abstract =     "Microarray data provides information on gene
                 expression levels of thousands of genes in a cell in a
                 single experiment. DNA microarray is a powerful tool in
                 the diagnosis of cancer. Numerous efforts have been
                 made to use gene expression profiles to improve
                 precision of tumor classification. In this study
                 comparison between class prediction accuracy of two
                 different classifiers, Genetic Programming and
                 Genetically Evolved Decision Trees, was carried out
                 using the best 10 and best 20 genes ranked by the
                 t-statistic and mutual information. Genetic Programming
                 proved out to be the better classifier for this dataset
                 based on area under the receiver operating
                 characteristic curve (AUC) and total accuracy using
                 mutual information based feature selection. We conclude
                 that Genetic Programming together with mutual
                 information based feature selection is the most
                 efficient alternative to the existing colon cancer
                 prediction techniques.",
}

Genetic Programming entries for Ashwinikumar Kulkarni B S C Naveen Kumar Vadlamani Ravi Upadhyayula Suryanarayana N Murthy

Citations