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Bayesian network classification of gastrointestinal bleeding


Nazziwa Aisha, and Adam, Mohd Bakri and Shohaimi, Shamarina and Mustapha, Aida (2014) Bayesian network classification of gastrointestinal bleeding. Pertanika Journal of Science & Technology, 22 (2). pp. 567-575. ISSN 0128-7680; ESSN: 2231-8526

Abstract / Synopsis

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 identifying the source of GIB in the absence of hematemesis. Data of 325 patients admitted via the emergency department (ED) for GIB without hematemesis and who underwent confirmatory testing were analysed. Six attributes related to demography and their presenting signs were chosen. NBC was used to calculate the conditional probability of an individual being assigned to Upper Gastrointestinal bleeding (UGIB) or Lower Gastrointestinal bleeding (LGIB). High classification accuracy (87.3 %), specificity (0.85) and sensitivity (0.88) were achieved. NBC is a useful tool to support the identification of the source of gastrointestinal bleeding in patients without hematemesis.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Publisher: Universiti Putra Malaysia Press
Keywords: Bayesian network classifiers; Data mining; Emergency department; Hematemesis; Lower gastrointestinal bleeding; Naive bayes classifier; Upper gastrointestinal bleeding
Depositing User: Najah Mohd Ali
Date Deposited: 27 Nov 2015 09:11
Last Modified: 27 Nov 2015 09:11
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