Volume 9 - Issue 4
A Belief Rule Based Expert System to Assess Hypertension under Uncertainty
- Mohammad Shahadat Hossain
Dept. of Computer Science & Engineering, University of Chittagong, Bangladesh
hossain ms@cu.ac.bd
- Fatema-Tuj-Johora
Dept. of Computer Science & Engineering, University of Chittagong, Bangladesh
inna.johora@gmail.com
- Karl Andersson
Pervasive and Mobile Computing Laboratory, Lulea University of Technology, Skelleftea, Sweden
karl.andersson@ltu.se
Keywords: Expert System, Belief Rule Base, Hypertension, Uncertainty, Knowledge Base
Abstract
Hypertension (HPT) plays an important role, especially for stroke and heart diseases. Therefore, the
accurate assessment of hypertension is becoming a challenge. However, the presence of uncertainties,
associated with the signs and symptoms of HPT are becoming crucial to conduct the precise
assessment. This article presents a web-based expert system (web BRBES) by employing belief
rule based (BRB) methodology to assess HPT, allowing the generation of reliable results. In order to
check the reliability of the system, a comparison has been performed among various approaches such
as decision tree, random forest, artificial neural networks, fuzzy rule based expert system and experts’
opinion. Different performance metrics such as confusion matrix, accuracy, root mean square error,
area under curve have been used to contrast the reliability of the approaches. The BRBES produces
a more reliable result than from the other approaches. Moreover, the user friendliness of the web
BRBES found high as obtained by using the PACT (People, Activities, Contexts, Technologies) approach
over 200 people.