@inproceedings{a1bf14cb661643c388dfe1ceb81230d8,
title = "Bayesian classifiers for predicting the outcome of breast cancer preoperative chemotherapy",
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.",
author = "Braga, {Ant{\^o}nio P.} and Horta, {Euler G.} and Ren{\'e} Natowicz and Roman Rouzier and Roberto Incitti and Rodrigues, {Thiago S.} and Costa, {Marcelo A.} and Pataro, {Carmen D.M.} and Arben {\c C}ela",
year = "2008",
doi = "10.1007/978-3-540-69939-2_25",
language = "English (US)",
isbn = "3540699384",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "263--266",
booktitle = "Artificial Neural Networks in Pattern Recognition - Third IAPR Workshop, ANNPR 2008, Proceedings",
address = "Germany",
note = "3rd IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008 ; Conference date: 02-07-2008 Through 04-07-2008",
}