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Title: Classification of ovarian tumor using Bayesian least squares support vector machines
Other Titles: Lectures Notes in Artificial Intelligence, vol. 2780
Authors: Lu, Chuan
Van Gestel, Tony
Suykens, Johan
Van Huffel, Sabine
Vergote, Ignace
Timmerman, Dirk #
Issue Date: 2003
Publisher: Springer Verlag
Host Document: Lecture Notes in Artificial Intelligence pages:219-228
Conference: Conference on Artificial Intelligence in Medicine in Europe (AIME 2003) edition:9th location:Protaras, Cyprus date:2003
Abstract: The aim of this study is to develop the Bayesian Least Squares Support Vector Machine (LS-SVM) classifiers for preoperative discrimination between benign and malignant ovarian tumors. We describe how to perform (hyper)parameter estimation, input variable selection for LS-SVMs within the evidence framework. The issue of computing the posterior class probability for risk minimization decision making is addressed. The performance of the LS-SVM models with linear and RBF kernels has been evaluated and compared with Bayesian multi-layer perceptrons (MLPs) and linear discriminant analysis.
Description: \emph{Artificial Intelligence in Medicine}, (Dojat M., Keravnou E., and Barahona P., eds.), Proc. of the 9th Conference on Artificial Intelligence in Medicine in Europe (AIME 2003), Protaras, Cyprus, October 2003, vol. 2780 of \emph{Lecture Notes in Artificial Intelligence}, Springer-Verlag, 2003
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Gynaecological Oncology
Section Woman - Miscellaneous (-)
# (joint) last author

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