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Using Bayesian Network Inference to Modeling Lung Cancer Diagnosis

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dc.contributor.author Elamin, Yousra ElfatihYousif Mohammed
dc.contributor.author Supervisor - Eltahir Mohammed Houssien
dc.date.accessioned 2014-12-17T07:52:43Z
dc.date.available 2014-12-17T07:52:43Z
dc.date.issued 2014-05-20
dc.identifier.citation Elamin,Yousra ElfatihYousif Mohammed.Using Bayesian Network Inference to Modeling Lung Cancer Diagnosis/Yousra ElfatihYousifM.Elamin;Eltahir Mohammed Houssien.-khartoum:Sudan University of Science and Technology,College of Engineering,2014.-57p:ill;28cm.-M.Sc. en_US
dc.identifier.uri http://repository.sustech.edu/handle/123456789/8990
dc.description thesis en_US
dc.description.abstract This study subjective to deal with probabilistic inference of lung cancer diagnosis involving features that are not directly related, and for which the conditional probability cannot be readily computed using a simple application of the Bayes' theorem that illustrates a simple Bayesian Network example for exact probabilistic inference using Pearl's message-passing algorithm to model the diagnostic of lung cancer. The model of diagnosis examined over 200 patients and the results were been satisfied. en_US
dc.description.sponsorship Sudan University of Science and Technology en_US
dc.language.iso en en_US
dc.publisher Sudan University of Science and Technology en_US
dc.subject Biomedical Engineering en_US
dc.subject Bayesian Network en_US
dc.subject Inference to Modeling Lung en_US
dc.subject Cancer Diagnosis en_US
dc.title Using Bayesian Network Inference to Modeling Lung Cancer Diagnosis en_US
dc.type Thesis en_US


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