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A Belief Rule Based Expert System to
Assess Hypertension Mohammad Shahadat Hossain1,
Fatema-Tuj-Johora1, and Karl Andersson2+ 1Dept.
of Computer Science & Engineering, University of Chittagong, Bangladesh hossain_ms@cu.ac.bd, inna.johora@gmail.com 2Pervasive
and Mobile Computing Laboratory, Luleć
University of Technology, Skellefteć, Sweden karl.andersson@ltu.se 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. Keywords: Expert System, Belief Rule Base, Hypertension,
Uncertainty, Knowledge Base +: Corresponding
author: Karl Andersson Pervasive and Mobile Computing Laboratory, Luleć University of Technology, Skellefteć, Sweden, Journal
of Internet Services and Information Security
(JISIS), 9(4): 18-38,
November 2019 DOI: 10.22667/JISIS.2019.11.30.018 [pdf] |