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Model based Investigation of Pandemic Influenza

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dc.contributor.author Aung, Ei Ei
dc.contributor.author San, Khin Moe
dc.date.accessioned 2019-07-24T15:52:53Z
dc.date.available 2019-07-24T15:52:53Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1250
dc.description.abstract A pandemic is an epidemic of human disease occurring over a very wide area, crossing international boundaries and affecting a large number of people. Influenza is a virus that causes respiratory disease in humans, with typical symptoms of fever, cough, and muscle ache and pneumonia and death. This system can learn the patterns using Bayesian Analysis and develop a Decision Support System. Bayesian Classifier is based on the theorem of posterior probability. Calculate the probability when the new case comes. Computer-based medical systems are playing an increasing relevant role in assisting both diagnosis and treatments. This paper intends to develop Bayesian Classification method for flu diagnosis based on the symptoms of the patients. This system stores the knowledge of the medical experts and the medical record. Based on the knowledge stored, the system can learn the pattern using Bayesian Analysis and decides the probability when the new case comes. To develop a Decision Support System for automatic classification method for Pandemic Influenza based on symptom of the patients. Decision support system is also used for the patient who tests themselves at home instead of clinical test. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject Bayes' Theorem en_US
dc.subject Classifier Accuracy en_US
dc.subject Decision Support Systems (DSS) en_US
dc.title Model based Investigation of Pandemic Influenza en_US
dc.type Article en_US


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