Genetic Programming as a Method to Develop Powerful Predictive Models for Clinical Diagnosis

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@InProceedings{Siccama:gecco05ws,
  author =       "Ivar Siccama and Maarten Keijzer",
  title =        "Genetic Programming as a Method to Develop Powerful
                 Predictive Models for Clinical Diagnosis",
  booktitle =    "Genetic and Evolutionary Computation Conference
                 {(GECCO2005)} workshop program",
  year =         "2005",
  month =        "25-29 " # jun,
  editor =       "Franz Rothlauf and Misty Blowers and 
                 J{\"u}rgen Branke and Stefano Cagnoni and Ivan I. Garibay and 
                 Ozlem Garibay and J{\"o}rn Grahl and Gregory Hornby and 
                 Edwin D. {de Jong} and Tim Kovacs and Sanjeev Kumar and 
                 Claudio F. Lima and Xavier Llor{\`a} and 
                 Fernando Lobo and Laurence D. Merkle and Julian Miller and 
                 Jason H. Moore and Michael O'Neill and Martin Pelikan and 
                 Terry P. Riopka and Marylyn D. Ritchie and Kumara Sastry and 
                 Stephen L. Smith and Hal Stringer and 
                 Keiki Takadama and Marc Toussaint and Stephen C. Upton and 
                 Alden H. Wright",
  publisher =    "ACM Press",
  address =      "Washington, D.C., USA",
  keywords =     "genetic algorithms, genetic programming",
  pages =        "164--166",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005wks/papers/0164.pdf",
  abstract =     "In the field of medicine it is of vital importance to
                 accurately predict the presence of a disease
                 (diagnostic prediction)or the future occurrence of a
                 certain event (prognostic prediction). Genetic
                 programming provides a method to develop such
                 prediction models in an optimal way. We discuss as an
                 example the diagnostic prediction of pulmonary embolism
                 (PE),and compare the method of genetic programming with
                 the logistic regression technique, which is well-known
                 in the medical field.",
  notes =        "Distributed on CD-ROM at GECCO-2005. ACM
                 1-59593-097-3/05/0006",
}

Genetic Programming entries for Ivar Siccama Maarten Keijzer

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