Breast cancer detection using cartesian genetic programming evolved artificial neural networks

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Arbab Masood Ahmad and Gul Muhammad Khan and 
                 Sahibzada Ali Mahmud and Julian Francis Miller",
  title =        "Breast cancer detection using cartesian genetic
                 programming evolved artificial neural networks",
  booktitle =    "GECCO '12: Proceedings of the fourteenth international
                 conference on Genetic and evolutionary computation
  year =         "2012",
  editor =       "Terry Soule and Anne Auger and Jason Moore and 
                 David Pelta and Christine Solnon and Mike Preuss and 
                 Alan Dorin and Yew-Soon Ong and Christian Blum and 
                 Dario Landa Silva and Frank Neumann and Tina Yu and 
                 Aniko Ekart and Will Browne and Tim Kovacs and 
                 Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and 
                 Giovanni Squillero and Nicolas Bredeche and 
                 Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and 
                 Martin Pelikan and Silja Meyer-Nienberg and 
                 Christian Igel and Greg Hornby and Rene Doursat and 
                 Steve Gustafson and Gustavo Olague and Shin Yoo and 
                 John Clark and Gabriela Ochoa and Gisele Pappa and 
                 Fernando Lobo and Daniel Tauritz and Jurgen Branke and 
                 Kalyanmoy Deb",
  isbn13 =       "978-1-4503-1177-9",
  pages =        "1031--1038",
  keywords =     "genetic algorithms, genetic programming, real world
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Philadelphia, Pennsylvania, USA",
  DOI =          "doi:10.1145/2330163.2330307",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "A fast learning neuro-evolutionary technique that
                 evolves Artificial Neural Networks using Cartesian
                 Genetic Programming (CGPANN) is used to detect the
                 presence of breast cancer. Features from breast mass
                 are extracted using fine needle aspiration (FNA) and
                 are applied to the CGPANN for diagnosis of breast
                 cancer. FNA data is obtained from the Wisconsin
                 Diagnostic Breast Cancer website and is used for
                 training and testing the network. The developed system
                 produces fast and accurate results when compared to
                 contemporary work done in the field. The error of the
                 model comes out to be as low as 1percent for Type-I
                 (classifying benign sample falsely as malignant) and
                 0.5percent for Type-II (classifying malignant sample
                 falsely as benign).",
  notes =        "Also known as \cite{2330307} GECCO-2012 A joint
                 meeting of the twenty first international conference on
                 genetic algorithms (ICGA-2012) and the seventeenth
                 annual genetic programming conference (GP-2012)",

Genetic Programming entries for Arbab Masood Ahmad Gul Muhammad Khan Sahibzada Ali Mahmud Julian F Miller