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
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
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| Status: |
Published |
| Creators/Authors: |
|
| 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: |
26 Dec 2021 13:55 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/22168 |
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