Literature DB >> 17702292

Explanation of Bayesian networks and influence diagrams in Elvira.

Carmen Lacave1, Manuel Luque, Francisco Javier Díez.   

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.

Mesh:

Year:  2007        PMID: 17702292     DOI: 10.1109/tsmcb.2007.896018

Source DB:  PubMed          Journal:  IEEE Trans Syst Man Cybern B Cybern        ISSN: 1083-4419


  3 in total

1.  Development of Interpretable Predictive Models for BPH and Prostate Cancer.

Authors:  Pablo Bermejo; Alicia Vivo; Pedro J Tárraga; J A Rodríguez-Montes
Journal:  Clin Med Insights Oncol       Date:  2015-02-25

2.  From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.

Authors:  Anthony Costa Constantinou; Norman Fenton; William Marsh; Lukasz Radlinski
Journal:  Artif Intell Med       Date:  2016-01-16       Impact factor: 5.326

3.  Optimal sequence of tests for the mediastinal staging of non-small cell lung cancer.

Authors:  Manuel Luque; Francisco Javier Díez; Carlos Disdier
Journal:  BMC Med Inform Decis Mak       Date:  2016-01-26       Impact factor: 2.796

  3 in total

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