Explanation of Bayesian networks and influence diagrams in Elvira

Carmen Lacave; Manuel Luque; Francisco Javier Díez

doi:10.1109/tsmcb.2007.896018

Explanation of Bayesian networks and influence diagrams in Elvira

IEEE Trans Syst Man Cybern B Cybern. 2007 Aug;37(4):952-65. doi: 10.1109/tsmcb.2007.896018.

Authors

Carmen Lacave¹, Manuel Luque, Francisco Javier Díez

Affiliation

¹ Department of Technology and Information Systems, University of Castilla-La Mancha, 13071 Ciudad Real, Spain. carmen.lacave@uclm.es

PMID: 17702292
DOI: 10.1109/tsmcb.2007.896018

Abstract

Bayesian networks (BNs) and influence diagrams (IDs) are probabilistic graphical models that are widely used for building diagnosis- and decision-support expert systems. Explanation of both the model and the reasoning is important for debugging these models, alleviating users' reluctance to accept their advice, and using them as tutoring systems. This paper describes some explanation options for BNs and IDs that have been implemented in Elvira and how they have been used for building medical models and teaching probabilistic reasoning to pre- and postgraduate students.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Artificial Intelligence
Bayes Theorem*
Computer Simulation
Decision Support Techniques*
Models, Theoretical*
Neural Networks, Computer*
Pattern Recognition, Automated / methods*
Software*