Using genetic programming to classify node positive patients in bladder cancer

Arpit A. Almal, Anirban P. Mitra, Ram H. Datar, Peter F. Lenehan, David W. Fry, Richard J. Cote, William P. Worzel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Nodal staging has been identified as an independent indicator of prognosis. Quantitative RT-PCR data was taken for 70 genes associated with bladder cancer and genetic programming was used to develop classification rules associated with nodal stages of bladder cancer. This study suggests involvement of several key genes for discriminating between samples with and without nodal metastasis.

Original languageEnglish
Title of host publicationGECCO 2006 - Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery
Pages239-246
Number of pages8
ISBN (Print)1595931864, 9781595931863
DOIs
StatePublished - 2006
Event8th Annual Genetic and Evolutionary Computation Conference 2006 - Seattle, WA, United States
Duration: Jul 8 2006Jul 12 2006

Publication series

NameGECCO 2006 - Genetic and Evolutionary Computation Conference
Volume1

Conference

Conference8th Annual Genetic and Evolutionary Computation Conference 2006
Country/TerritoryUnited States
CitySeattle, WA
Period07/8/0607/12/06

Keywords

  • Bladder cancer
  • Classification
  • Feature selection
  • Genetic Programming
  • Machine Learning
  • Nodal staging

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