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
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5064)

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.

Keywords

Preoperative Chemotherapy Pathologic Complete Response Minority Class Bayesian Classifier Training Case 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Antônio P. Braga
    • 1
  • Euler G. Horta
    • 1
  • René Natowicz
    • 2
  • Roman Rouzier
    • 3
  • Roberto Incitti
    • 4
  • Thiago S. Rodrigues
    • 5
  • Marcelo A. Costa
    • 1
  • Carmen D. M. Pataro
    • 1
  • Arben Çela
    • 2
  1. 1.Depto. Engenharia EletrônicaUniversidade Federal de Minas GeraisBrazil
  2. 2.Université Paris-EstESIEE-ParisFrance
  3. 3.Hôpital Tenon, Service de gynécologieFrance
  4. 4.Institut Mondor de Médecine MoléculairePlate-forme génomiqueFrance
  5. 5.Depto. Ciência da ComputaçãoUniversidade Federal de LavrasBrazil

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