A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion

Mohammad Shahadat Hossain, Emran Hossain, Md. Saifuddin Khalid, Mohammad Ahsanul Haque

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

28 Downloads (Pure)

Abstract

Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty such as vagueness; imprecision; randomness; ignorance and incompleteness. Consequently; traditional disease diagnosis; which is performed by a physician; cannot deliver accurate results. Therefore; this paper presents the design; development and application of a decision support system for assessing asthma under conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system.
Original languageEnglish
Title of host publicationProceedings from Scandinavian Conference on Health Informatics
EditorsCarl Erik Moe, Mariann Fossum
Number of pages7
PublisherLinköping University Electronic Press
Publication date2014
Pages83-89
Article number012
ISBN (Print)978-91-7519-241-3
Publication statusPublished - 2014
EventScandinavian Conference on Health Informatics - University of Agder, Grimstad, Norway
Duration: 21 Aug 201422 Aug 2014

Conference

ConferenceScandinavian Conference on Health Informatics
LocationUniversity of Agder
CountryNorway
CityGrimstad
Period21/08/201422/08/2014
SeriesLinköping Electronic Conference Proceedings
ISSN1650-3686

Fingerprint

Decision support systems
Expert systems
Knowledge representation
Uncertainty

Keywords

  • Belief Rule Base
  • Uncertainty
  • RIMER
  • Asthma
  • Suspicion
  • Decision Support System
  • Inference

Cite this

Hossain, M. S., Hossain, E., Khalid, M. S., & Haque, M. A. (2014). A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion. In C. E. Moe, & M. Fossum (Eds.), Proceedings from Scandinavian Conference on Health Informatics (pp. 83-89). [012] Linköping University Electronic Press. Linköping Electronic Conference Proceedings
Hossain, Mohammad Shahadat ; Hossain, Emran ; Khalid, Md. Saifuddin ; Haque, Mohammad Ahsanul. / A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion. Proceedings from Scandinavian Conference on Health Informatics. editor / Carl Erik Moe ; Mariann Fossum. Linköping University Electronic Press, 2014. pp. 83-89 (Linköping Electronic Conference Proceedings).
@inproceedings{97fa34c130d94ba7b02ff996ff0387ab,
title = "A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion",
abstract = "Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty such as vagueness; imprecision; randomness; ignorance and incompleteness. Consequently; traditional disease diagnosis; which is performed by a physician; cannot deliver accurate results. Therefore; this paper presents the design; development and application of a decision support system for assessing asthma under conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system.",
keywords = "Belief Rule Base, Uncertainty, RIMER, Asthma, Suspicion, Decision Support System, Inference",
author = "Hossain, {Mohammad Shahadat} and Emran Hossain and Khalid, {Md. Saifuddin} and Haque, {Mohammad Ahsanul}",
year = "2014",
language = "English",
isbn = "978-91-7519-241-3",
series = "Link{\"o}ping Electronic Conference Proceedings",
pages = "83--89",
editor = "Moe, {Carl Erik} and Mariann Fossum",
booktitle = "Proceedings from Scandinavian Conference on Health Informatics",
publisher = "Link{\"o}ping University Electronic Press",

}

Hossain, MS, Hossain, E, Khalid, MS & Haque, MA 2014, A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion. in CE Moe & M Fossum (eds), Proceedings from Scandinavian Conference on Health Informatics., 012, Linköping University Electronic Press, Linköping Electronic Conference Proceedings, pp. 83-89, Scandinavian Conference on Health Informatics, Grimstad, Norway, 21/08/2014.

A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion. / Hossain, Mohammad Shahadat ; Hossain, Emran; Khalid, Md. Saifuddin; Haque, Mohammad Ahsanul.

Proceedings from Scandinavian Conference on Health Informatics. ed. / Carl Erik Moe; Mariann Fossum. Linköping University Electronic Press, 2014. p. 83-89 012 (Linköping Electronic Conference Proceedings).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

T1 - A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion

AU - Hossain, Mohammad Shahadat

AU - Hossain, Emran

AU - Khalid, Md. Saifuddin

AU - Haque, Mohammad Ahsanul

PY - 2014

Y1 - 2014

N2 - Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty such as vagueness; imprecision; randomness; ignorance and incompleteness. Consequently; traditional disease diagnosis; which is performed by a physician; cannot deliver accurate results. Therefore; this paper presents the design; development and application of a decision support system for assessing asthma under conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system.

AB - Asthma is a common chronic disease that affects millions of people around the world. The most common signs and symptoms of asthma are cough; breathlessness; wheeze; chest tightness and respiratory rate. They cannot be measured accurately since they consist of various types of uncertainty such as vagueness; imprecision; randomness; ignorance and incompleteness. Consequently; traditional disease diagnosis; which is performed by a physician; cannot deliver accurate results. Therefore; this paper presents the design; development and application of a decision support system for assessing asthma under conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system.

KW - Belief Rule Base

KW - Uncertainty

KW - RIMER

KW - Asthma

KW - Suspicion

KW - Decision Support System

KW - Inference

M3 - Article in proceeding

SN - 978-91-7519-241-3

T3 - Linköping Electronic Conference Proceedings

SP - 83

EP - 89

BT - Proceedings from Scandinavian Conference on Health Informatics

A2 - Moe, Carl Erik

A2 - Fossum, Mariann

PB - Linköping University Electronic Press

ER -

Hossain MS, Hossain E, Khalid MS, Haque MA. A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion. In Moe CE, Fossum M, editors, Proceedings from Scandinavian Conference on Health Informatics. Linköping University Electronic Press. 2014. p. 83-89. 012. (Linköping Electronic Conference Proceedings).