e-ISSN 2231-8542
ISSN 1511-3701

Home / Regular Issue / JTAS Vol. 22 (2) Jul. 2014 / JST-0461-2012


Bayesian Network Classification of Gastrointestinal Bleeding

Nazziwa Aisha, Mohd Bakri Adam, Shamarina Shohaimi1 and Aida Mustapha

Pertanika Journal of Tropical Agricultural Science, Volume 22, Issue 2, July 2014

Keywords: Bayesian network classifiers, Emergency department, hematemesis, upper gastrointestinal bleeding, Naive Bayes classifier, lower gastrointestinal bleeding, data mining

Published on:

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.

ISSN 1511-3701

e-ISSN 2231-8542

Article ID


Download Full Article PDF

Share this article

Recent Articles