Cartesian Genetic Programming and its Application to Medical Diagnosis

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Stephen L. Smith",
  title =        "Cartesian Genetic Programming and its Application to
                 Medical Diagnosis",
  journal =      "IEEE Computational Intelligence Magazine",
  year =         "2011",
  month =        nov,
  volume =       "6",
  number =       "4",
  pages =        "56--67",
  size =         "12 pages",
  abstract =     "Cartesian Genetic Programming (CGP) is a form of
                 genetic programming that is flexible and adaptable to a
                 range of problems. In this article, a particular
                 representation of CGP, known as implicit context
                 representation CGP is presented and its application to
                 two medical conditions: the diagnosis of Parkinson'
                 disease and the detection of breast cancer from
                 mammograms. CGP has a number of advantages over
                 conventional genetic programming and is well suited to
                 the highly non-linear problems considered here. Summary
                 results are presented for the application of CGP to
                 real patient data that are sufficiently encouraging to
                 warrant further clinical trials which are currently in
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, CGP, Parkinson disease, breast
                 cancer detection, context representation, mammograms,
                 medical diagnosis application, diseases, mammography,
                 medical computing, patient diagnosis",
  DOI =          "doi:10.1109/MCI.2011.942583",
  ISSN =         "1556-603X",
  notes =        "Also known as \cite{6052376}",

Genetic Programming entries for Stephen L Smith