A Belief Rule Based Expert System to Assess Mental Disorder under Uncertainty

Mohammad Shahadat Hossain, Ahmed Afif Monrat, Mamun Hasan, Razuan Karim, Tanveer Ahmed Bhuiyan, Md. Saifuddin Khalid

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

11 Citations (Scopus)


Mental disorder is a change of mental or behavioral pattern that causes sufferings and impairs the ability to function in ordinary life. In psychopathology, the assessment methods of mental disorder contain various types of uncertainties associated with signs and symptoms. This study identifies a method that addresses the issue of uncertainty in assessing mental disorder. The fuzzy logic knowledge representation schema can address uncertainty associated with linguistic terms including ambiguity, imprecision, and vagueness. However, fuzzy logic is incapable of addressing uncertainty due to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema in this BRBES. The study shows that the results generated by BRBES are more reliable than that of Fuzzy Rule-based expert system and from a human expert.
Original languageEnglish
Title of host publicationProceedings of International Conference on Informatics, Electronics & Vision (ICIEV), 2016
Number of pages6
Publication date2016
Pages1089 - 1094
ISBN (Electronic)978-1-5090-1270-1, 978-1-5090-1269-5
Publication statusPublished - 2016
EventInformatics, Electronics & Vision (ICIEV), 2016 International Conference on - Dhaka, Bangladesh
Duration: 13 May 201614 May 2016


ConferenceInformatics, Electronics & Vision (ICIEV), 2016 International Conference on
Internet address


  • Mental disorders
  • Medical services
  • Psychology
  • Fuzzy logic
  • Cognition
  • Expert systems
  • Uncertainty


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