Bayesian network modeling aspects resulting from applications in medical diagnostics and GSM troubleshooting

Authors:
Ruxandra Lupas Scheiterer;Dragan Obradovic
Affiliations:
Siemens AG, Corporate Technology, Information and Communications;Siemens AG, Corporate Technology, Information and Communications
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

Citing 3
Cited 1

Introduction to Bayesian Networks

Introduction to Bayesian Networks
Knowledge Acquisition and Automated Generation of Bayesian Networks for a Medical Dialogue and Advisory System

AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
Troubleshooting in GSM mobile telecommunication networks based on domain model and sensory information

ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II

Troubleshooting in GSM mobile telecommunication networks based on domain model and sensory information

ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II

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Abstract

This paper addresses issues in constructing a Bayesian Network (BN) domain model for diagnostic purposes from expert knowledge. The novelty of this paper is the approach for structured generation of a model that incorporates the unstructured multifaceted and possibly conflicting probabilistic information provided by the experts.