Cart (Loading....) | Create Account
Close category search window

Mutual Information Preconditioning Improves Structure Learning of Bayesian Networks From Medical Databases

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Meloni, A. ; Inst. of Clinical Physiol., Nat. Res. Council (CNR), Pisa, Italy ; Ripoli, A. ; Positano, V. ; Landini, L.

Bayesian networks (BNs) represent one of the most successful tools for medical diagnosis, selection of the optimal treatment, and prediction of the treatment outcome. In this paper, we present an algorithm for BN structure learning, which is a variation of the standard search-and-score approach. The proposed algorithm overcomes the creation of redundant network structures that may include nonsignificant connections between variables. In particular, the algorithm finds what relationships between the variables must be prevented, by exploiting the binarization of a square matrix containing the mutual information (MI) among all pairs of variables. Two different binarization methods are implemented. The first one is based on the maximum relevance minimum redundancy selection strategy. The second one uses a threshold. The MI binary matrix is exploited as a preconditioning step for the subsequent greedy search procedure that optimizes the network score, reducing the number of possible search paths in the greedy search. Our algorithm has been tested on two different medical datasets and compared against the standard search-and-score algorithm as implemented in the DEAL package.

Published in:

Information Technology in Biomedicine, IEEE Transactions on  (Volume:13 ,  Issue: 6 )

Date of Publication:

Nov. 2009

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.