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Impact of Bayesian network model structure on the accuracy of medical diagnostic systems

Oniśko, A and Druzdzel, MJ (2014) Impact of Bayesian network model structure on the accuracy of medical diagnostic systems. In: UNSPECIFIED UNSPECIFIED, 167 - 178. ISBN 9783319071756

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Abstract

While Bayesian network models may contain a handful of numerical parameters that are important for their quality, several empirical studies have confirmed that overall precision of their probabilities is not crucial. In this paper, we study the impact of the structure of a Bayesian network on the precision of medical diagnostic systems. We show that also the structure is not that important - diagnostic accuracy of several medical diagnostic models changes minimally when we subject their structures to such transformations as arc removal and arc reversal. © 2014 Springer International Publishing.


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Details

Item Type: Book Section
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Oniśko, A
Druzdzel, MJdruzdzel@pitt.eduDRUZDZEL
Date: 1 January 2014
Date Type: Publication
Journal or Publication Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 8468 L
Number: PART 2
Page Range: 167 - 178
Event Type: Conference
DOI or Unique Handle: 10.1007/978-3-319-07176-3_15
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9783319071756
ISSN: 0302-9743
Date Deposited: 02 Jul 2014 17:03
Last Modified: 08 Dec 2017 13:55
URI: http://d-scholarship.pitt.edu/id/eprint/22168

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