Literature DB >> 27066596

ExpertBayes: Automatically refining manually built Bayesian networks.

Ezilda Almeida1, Pedro Ferreira2, Tiago Vinhoza3, Inês Dutra2, Jingwei Li4, Yirong Wu4, Elizabeth Burnside4.   

Abstract

Bayesian network structures are usually built using only the data and starting from an empty network or from a naïve Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be automatically or manually refined in search for better performance models. In this work, we take Bayesian networks built by specialists and show that minor perturbations to this original network can yield better classifiers with a very small computational cost, while maintaining most of the intended meaning of the original model.

Entities:  

Keywords:  advice-based systems; bayesian networks; learning bayesian network structures

Year:  2014        PMID: 27066596      PMCID: PMC4826063          DOI: 10.1109/ICMLA.2014.64

Source DB:  PubMed          Journal:  Proc Int Conf Mach Learn Appl


  2 in total

1.  Predicting malignancy from mammography findings and image-guided core biopsies.

Authors:  Pedro Ferreira; Nuno A Fonseca; Inês Dutra; Ryan Woods; Elizabeth Burnside
Journal:  Int J Data Min Bioinform       Date:  2015       Impact factor: 0.667

2.  Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings.

Authors:  Elizabeth S Burnside; Jesse Davis; Jagpreet Chhatwal; Oguzhan Alagoz; Mary J Lindstrom; Berta M Geller; Benjamin Littenberg; Katherine A Shaffer; Charles E Kahn; C David Page
Journal:  Radiology       Date:  2009-04-14       Impact factor: 11.105

  2 in total

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