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.
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Braga, A.P. et al. (2008). Bayesian Classifiers for Predicting the Outcome of Breast Cancer Preoperative Chemotherapy. In: Prevost, L., Marinai, S., Schwenker, F. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2008. Lecture Notes in Computer Science(), vol 5064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69939-2_25
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DOI: https://doi.org/10.1007/978-3-540-69939-2_25
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