Non-parametric kernel density estimation for the prediction of neoadjuvant chemotherapy outcomes
In this paper we propose an application of local statistical models to the problem of identifying patients with pathologic complete response (PCR) to neoadjuvant chemotherapy. The idea of using local models is to split the input space (with data from PCR and NoPCR patients) and build a model for eac...
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Veröffentlicht in: | 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology 2010-01, Vol.2010, p.1775-1778 |
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Sprache: | eng |
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Zusammenfassung: | In this paper we propose an application of local statistical models to the problem of identifying patients with pathologic complete response (PCR) to neoadjuvant chemotherapy. The idea of using local models is to split the input space (with data from PCR and NoPCR patients) and build a model for each partition. After the construction of the models we used bayesian classifiers and logistic regression to classify patients in the two classes. |
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ISSN: | 1094-687X 1557-170X 1558-4615 |
DOI: | 10.1109/IEMBS.2010.5626748 |