Bayesian classifiers for predicting the outcome of breast cancer preoperative chemotherapy

Antônio P. Braga, Euler G. Horta, René Natowicz, Roman Rouzier, Roberto Incitti, Thiago S. Rodrigues, Marcelo A. Costa, Carmen D.M. Pataro, Arben Çela

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

2 Scopus citations

Abstract

Efficient predictors of the response to chemotherapy is an important issue because such predictors would make it possible to give the patients the most appropriate chemotherapy regimen. DNA microarrays appear to be of high interest for the design of such predictors. In this article we propose bayesian classifiers taking as input the expression levels of DNA probes, and a 'filtering' method for DNA probes selection.

Original languageEnglish (US)
Title of host publicationArtificial Neural Networks in Pattern Recognition - Third IAPR Workshop, ANNPR 2008, Proceedings
PublisherSpringer Verlag
Pages263-266
Number of pages4
ISBN (Print)3540699384, 9783540699385
DOIs
StatePublished - Jan 1 2008
Event3rd IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008 - Paris, France
Duration: Jul 2 2008Jul 4 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5064 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008
CountryFrance
CityParis
Period07/2/0807/4/08

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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