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A belief rule-based expert system to assess suspicion of acute coronary syndrome (ACS) under uncertainty
University of Chittagong, Bangladesh.ORCID-id: 0000-0002-7473-8185
International Islamic University Chittagong.
University of Chittagong, Bangladesh.
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0003-0244-3561
2018 (engelsk)Inngår i: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 22, nr 22, s. 7571-7586Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Acute coronary syndrome (ACS) is responsible for the obstruction of coronary arteries, resulting in the loss of lives. The onset of ACS can be determined by looking at the various signs and symptoms of a patient. However, the accuracy of ACS determination is often put into question since there exist different types of uncertainties with the signs and symptoms. Belief rule-based expert systems (BRBESs) are widely used to capture uncertain knowledge and to accomplish the task of reasoning under uncertainty by employing belief rule base and evidential reasoning. This article presents the process of developing a BRBES to determine ACS predictability. The BRBES has been validated against the data of 250 patients suffering from chest pain. It is noticed that the outputs created from the BRBES are more dependable than that of the opinion of cardiologists as well as other two expert system tools, namely artificial neural networks and support vector machine. Hence, it can be argued that the BRBES is capable of playing an important role in decision making as well as in avoiding costly laboratory investigations. A procedure to train the system, allowing its enhancement of performance, is also presented.

sted, utgiver, år, opplag, sider
Springer, 2018. Vol. 22, nr 22, s. 7571-7586
Emneord [en]
Acute coronary syndrome (ACS), Expert system, Belief rule base, Suspicion, Signs and symptoms, Uncertainty
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URN: urn:nbn:se:ltu:diva-64893DOI: 10.1007/s00500-017-2732-2ISI: 000448418300020Scopus ID: 2-s2.0-85025083671OAI: oai:DiVA.org:ltu-64893DiVA, id: diva2:1127806
Prosjekter
BRBWSN
Forskningsfinansiär
Swedish Research Council, 2014-4251
Merknad

Validerad;2018;Nivå 2;2018-10-15 (svasva)

Tilgjengelig fra: 2017-07-19 Laget: 2017-07-19 Sist oppdatert: 2018-12-04bibliografisk kontrollert

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Hossain, Mohammad ShahadatAndersson, Karl

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