A Belief Rule Based Expert System to Assess Hypertension under Uncertainty

Document identifier: oai:DiVA.org:ltu-77018
Access full text here:10.22667/JISIS.2019.11.30.018
Keyword: Natural Sciences, Computer and Information Sciences, Computer Sciences, Naturvetenskap, Data- och informationsvetenskap, Datavetenskap (datalogi), Media and Communication Technology, Medieteknik, Expert System, Belief Rule Base, Hypertension, Uncertainty, Knowledge Base, Pervasive Mobile Computing, Distribuerade datorsystem
Publication year: 2019
Relevant Sustainable Development Goals (SDGs):
SDG 9 Industry, innovation and infrastructureSDG 3 Good health and wellbeing
The SDG label(s) above have been assigned by OSDG.ai

Abstract:

Hypertension (HPT) plays an important role, especially for stroke and heart diseases. Therefore, theaccurate 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 preciseassessment. This article presents a web-based expert system (web BRBES) by employing beliefrule based (BRB) methodology to assess HPT, allowing the generation of reliable results. In order tocheck the reliability of the system, a comparison has been performed among various approaches suchas 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 producesa more reliable result than from the other approaches. Moreover, the user friendliness of the webBRBES found high as obtained by using the PACT (People, Activities, Contexts, Technologies) approach over 200 people.

Authors

Mohammad Shahadat Hossain

University of Chittagong, Bangladesh
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Fatema Tuj-Johora

University of Chittagong, Bangladesh
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Karl Andersson

Luleå tekniska universitet; Datavetenskap
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