Fuzzy reasoning for medical diagnosis-based aggregation on different ontologies

Hamido Fujita, I. Rudas, J. Fodor, Masaki Kurematsu, Jun Hakura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

The paper discusses reasoning application for decision making in medical diagnosis. This is to reason on medical concepts that are viewed on two type ontologies; namely physical and mental. We highlighted in this position paper issues on fuzzy reasoning by aggregating two types of ontologies that are used to formalize a patient state: mental ontology reflecting the patient mental behavior due to certain disorder and physical ontology reflecting the observed physical behavior exhibited through disorder. Similarity matching is used to find the similarity between fuzzy set reflected to mental fuzzy ontology, and physical fuzzy ontology. The alignment is projected on medical ontology to rank attributes for decision making. We apply aggregate function for ranking attributes related to physical object. In the same time, we apply harmonic power average aggregate function fuzzy for ranking attributes related to mental objects. The alignment of these two aggregate function produce weighted ranking order fuzzy set for medical decision making for diagnosis. The paper highlights these issues as new challenges extending intelligence reasoning of VDS.

Original languageEnglish
Title of host publicationSACI 2012 - 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings
Pages137-146
Number of pages10
Publication statusPublished - 2012
Event7th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2012 - Timisoara
Duration: May 24 2012May 26 2012

Other

Other7th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2012
CityTimisoara
Period5/24/125/26/12

Fingerprint

Ontology
Agglomeration
Decision making
Fuzzy sets

Keywords

  • Aggregate function
  • Cognitive model
  • Fuzzy reasoning
  • Human interaction
  • Medical diagnosis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Fujita, H., Rudas, I., Fodor, J., Kurematsu, M., & Hakura, J. (2012). Fuzzy reasoning for medical diagnosis-based aggregation on different ontologies. In SACI 2012 - 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings (pp. 137-146)

Fuzzy reasoning for medical diagnosis-based aggregation on different ontologies. / Fujita, Hamido; Rudas, I.; Fodor, J.; Kurematsu, Masaki; Hakura, Jun.

SACI 2012 - 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings. 2012. p. 137-146.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fujita, H, Rudas, I, Fodor, J, Kurematsu, M & Hakura, J 2012, Fuzzy reasoning for medical diagnosis-based aggregation on different ontologies. in SACI 2012 - 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings. pp. 137-146, 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2012, Timisoara, 5/24/12.
Fujita H, Rudas I, Fodor J, Kurematsu M, Hakura J. Fuzzy reasoning for medical diagnosis-based aggregation on different ontologies. In SACI 2012 - 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings. 2012. p. 137-146
Fujita, Hamido ; Rudas, I. ; Fodor, J. ; Kurematsu, Masaki ; Hakura, Jun. / Fuzzy reasoning for medical diagnosis-based aggregation on different ontologies. SACI 2012 - 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings. 2012. pp. 137-146
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