Now showing items 1-5 of 5
Bayesian Network Classification of Gastrointestinal Bleeding
(Universiti Putra Malaysia Press (Pertanika Journal of Science & Technology), 2014)
The source of gastrointestinal bleeding (GIB) remains uncertain in patients presenting without hematemesis. This paper aims at studying the accuracy, specificity and sensitivity of the Naive Bayesian Classifier (NBC) in ...
Classification models for predicting the source of gastrointestinal bleeding in the absence of hematemesis
(Basic Research Journal of Medicine and Clinical Sciences, 2013-08)
Management of acute gastrointestinal bleeding necessitates the identification of the source of bleed. The source of bleeding which is clear in patients presenting with hematemesis, is unclear in the absence of it. Logistic ...
On the Use of Bayesian Network Classifiers to Classify Patients with Peptic Ulcer Among Upper Gastrointestinal Bleeding Patients
A Bayesian network classifier is one type of graphical probabilistic models that is capable of representing relationship between variables in a given domain under study. We consider the naïve Bayes, tree augmented naïve ...
Effect of Missing Value Methods on Bayesian Network Classification of Hepatitis Data
(International Journal of Computer Science and Telecommunication, 2013-06)
Missing value imputation methods are widely used in solving missing value problems during statistical analysis. For classification tasks, these imputation methods can affect the accuracy of the Bayesian network classifiers. ...
Comparison of the Naive Bayes Classifier and Instance Based Learner in Classifying Upper Gastrointestinal Bleeding
Upper gastrointestinal bleeding is a medical emergence that results in high medical costs and death. Management of this disease requires ascertaining the cause of bleeding. The cause of bleeding is classified into esophageal ...