Disease modeling using Evolved Discriminate Function

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "James Cunha Werner and Tatiana Kalganova",
  title =        "Disease modeling using Evolved Discriminate Function",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2003",
  year =         "2003",
  editor =       "Conor Ryan and Terence Soule and Maarten Keijzer and 
                 Edward Tsang and Riccardo Poli and Ernesto Costa",
  volume =       "2610",
  series =       "LNCS",
  pages =        "465--474",
  address =      "Essex",
  publisher_address = "Berlin",
  month =        "14-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-00971-X",
  URL =          "http://www.geocities.com/jamwer2002/eurogp2003.pdf",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2610&spage=465",
  DOI =          "doi:10.1007/3-540-36599-0_44",
  abstract =     "Precocious diagnosis increases the survival time and
                 patient quality of life. It is a binary classification,
                 exhaustively studied in the literature. This paper
                 innovates proposing the application of genetic
                 programming to obtain a discriminate function. This
                 function contains the disease dynamics used to classify
                 the patients with as little false negative diagnosis as
                 possible. If its value is greater than zero then it
                 means that the patient is ill, otherwise healthy. A
                 graphical representation is proposed to show the
                 influence of each dataset attribute in the discriminate
                 function. The experiment deals with Breast Cancer and
                 Thrombosis and Collagen diseases diagnosis. The main
                 conclusion is that the discriminate function is able to
                 classify the patient using numerical clinical data, and
                 the graphical representation displays patterns that
                 allow understanding of the model.",
  notes =        "EuroGP'2003 held in conjunction with EvoWorkshops

Genetic Programming entries for James Cunha Werner Tatiana Kalganova