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FUZZY REASONING FOR MEDICAL DIAGNOSIS BASED AGGREGATION ON DIFFERENT ONTOLOGIES
- Prelegent(ci)
- Professor Hamido Fujita
- Afiliacja
- Iwate Prefectural University, Japan
- Termin
- 5 czerwca 2012 10:15
- Pokój
- p. 5820
- Seminarium
- Seminarium badawcze Zakładu Logiki: Wnioskowania aproksymacyjne w eksploracji danych
In this seminar I will discuss on issues related to 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. I will highlight 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 aggregate function for ranking attributes related to mental objects. The alignment of these two aggregate functions produce weighted ranking order fuzzy set for medical decision making for diagnosis. The paper highlights these issues as new challenges extending intelligence reasoning of Virtual Doctor System called as VDS.
