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A Belief Rule Based Expert System to Assess Hypertension under Uncertainty
University of Chittagong, Bangladesh.ORCID iD: 0000-0002-7473-8185
University of Chittagong, Bangladesh.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-0244-3561
2019 (English)In: Journal of Internet Services and Information Security (JISIS), ISSN 2182-2069, E-ISSN 2182-2077, Vol. 9, no 4, p. 18-38, article id 2Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Seoul, Republic of Korea: Innovative Information Science & Technology Research Group (ISYOU) , 2019. Vol. 9, no 4, p. 18-38, article id 2
Keywords [en]
Expert System, Belief Rule Base, Hypertension, Uncertainty, Knowledge Base
National Category
Computer Sciences Media and Communication Technology
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-77018DOI: 10.22667/JISIS.2019.11.30.018OAI: oai:DiVA.org:ltu-77018DiVA, id: diva2:1374462
Note

Validerad;2019;Nivå 1;2019-12-02 (johcin)

Available from: 2019-12-01 Created: 2019-12-01 Last updated: 2019-12-06Bibliographically approved

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