Expert system support using a Bayesian belief network for the classification of endometrial hyperplasia

2002 ◽  
Vol 197 (3) ◽  
pp. 403-414 ◽  
Author(s):  
M. L. Morrison ◽  
W. G. McCluggage ◽  
G. J. Price ◽  
J. Diamond ◽  
M. R. M. Sheeran ◽  
...  
Keyword(s):  
Expert System ◽  
Endometrial Hyperplasia ◽  
Bayesian Belief Network ◽  
System Support ◽  
Belief Network

scholarly journals Increasing Local Fish Consumption: A Bayesian Belief Network Analysis

2021 ◽  
Vol 33 (1) ◽  
pp. 104-121
Author(s):  
Samantha Paredes ◽  
Sean Pascoe ◽  
Louisa Coglan ◽  
Carol Richards
Keyword(s):  
Network Analysis ◽  
Fish Consumption ◽  
Bayesian Belief Network ◽  
Belief Network

Application of a Bayesian network to integrated circuit tester diagnosis

1995 ◽  
Vol 9 (1) ◽  
pp. 51-65 ◽  
Author(s):  
Daniel Mittelstadt ◽  
Robert Paasch ◽  
Bruce D’Ambrosio
Keyword(s):  
Expert System ◽  
Real World ◽  
Integrated Circuit ◽  
Procedural Knowledge ◽  
Knowledge Engineering ◽  
Bayesian Belief Network ◽  
Belief Networks ◽  
Diagnostic Problem ◽  
Ic Testing ◽  
Time Limitations

AbstractResearch efforts to implement a Bayesian belief-network-based expert system to solve a real-world diagnostic problem – the diagnosis of integrated circuit (IC) testing machines – are described. The development of several models of the IC tester diagnostic problem in belief networks also is described, the implementation of one of these models using symbolic probabilistic inference (SPI) is outlined, and the difficulties and advantages encountered are discussed. It was observed that modeling with interdependencies in belief networks simplifies the knowledge engineering task for the IC tester diagnosis problem, by avoiding procedural knowledge and focusing on the diagnostic component’s interdependencies. Several general model frameworks evolved through knowledge engineering to capture diagnostic expertise that facilitated expanding and modifying the networks. However, model implementation was restricted to a small portion of the modeling, that of contact resistance failures, which were due to time limitations and inefficiencies in the prototype inference software we used. Further research is recommended to refine existing methods, in order to speed evaluation of the models created in this research. With this accomplished, a more complete diagnosis can be achieved.

scholarly journals Estimating Survival in Patients with Operable Skeletal Metastases: An Application of a Bayesian Belief Network

PLoS ONE ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. e19956 ◽  
Author(s):  
Jonathan Agner Forsberg ◽  
John Eberhardt ◽  
Patrick J. Boland ◽  
Rikard Wedin ◽  
John H. Healey
Keyword(s):  
Bayesian Belief Network ◽  
Skeletal Metastases ◽  
Belief Network
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