Bayesian Gaussian network classifiers for mass spectra classification

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Title:	Bayesian Gaussian network classifiers for mass spectra classification
Author:	Bellón Molina, Víctor Manuel
Other authors:	Cerquides Bueno, Jesús
Abstract:	The early diagnosis of diseases in patients is a key objective of biomedical science and one of the most important factors in the treatment of diseases such as cancer. The early detection of cancer can make the di erence between a successful treatment and the dead of the patient. Ovarian cancer is diagnosed at late clinical stage in more than 80% of patients and the 5-year survival rate is around 35% of population, while in early diagnosed patients it exceeds 90%. The aim of this work is to present techniques for the early detection of ovarian cancers based in probabilistic analysis of proteomic spectra.
Subject(s):	-Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Diagnòstic per la imatge -Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica -Ovaries--Cancer--Diagnosis -Statistics--Graphic methods -Bayesian statistical decision theory -Ovaris--Càncer--Diagnòstic -Estadística--Mètodes gràfics -Estadística bayesiana
Rights:	Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Research/Master Thesis
Published by:	Universitat Politècnica de Catalunya
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