DocumentCode :
690497
Title :
Modified Full Bayesian Networks Classifiers for Medical Diagnosis
Author :
AlObaidi, Ahmed T. Sadiq ; Mahmood, Noor Thamer
Author_Institution :
Dept. of Comput. Sci., Univ. of Technol., Baghdad, Iraq
fYear :
2013
fDate :
23-24 Dec. 2013
Firstpage :
5
Lastpage :
12
Abstract :
This paper is present a modified Bayesian Network (BN) for Full Bayesian Classifier (FBC) for used it to diagnoses the condition of a patient from some of symptoms and medical history. The conditions are the heart diseases and the nervous diseases. Modified for FBC is depended on common structure known as naïve Bayes. Determining the network structure is D-separated by the variable. Each variable has CPT and each disease (table) has Probability. By modified the equation for find CPT for each variable and Probability for each disease (table) in Modified-FBC (M-FBC) structure, the system for diagnosis is designed. The experimental resulted show that the successful ratio of heart diseases (93%) and nervous system diseases (98%) approximately.
Keywords :
belief networks; diseases; medical diagnostic computing; pattern classification; probability; FBC; heart diseases; medical diagnosis; modified full Bayesian networks classifiers; naive Bayes structure; nervous diseases; network structure; patient condition; probability; Bayes methods; Diseases; Equations; Heart; Medical diagnostic imaging; Mutual information; Training data; Bayesian Network (BN); CPT; Full Bayesian Classifier (FBC); Modified-FBC (M-FBC); Probability; naïve Bayes);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Science Applications and Technologies (ACSAT), 2013 International Conference on
Conference_Location :
Kuching
Type :
conf
DOI :
10.1109/ACSAT.2013.10
Filename :
6836539
Link To Document :
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