Two types of ontology have been presented 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. The medical knowledge is represented by fuzzy attributes reflected on the medical knowledge. Aggregation function related to physical attributes represented as intuitionistic interval fuzzy weighted ordered average operators. Aggregation functions related to Bonferroni intuitionistic interval fuzzy weighted operators for mental ontology. Fuzzy representation based on these two types of ontology is aligned on medical knowledge for decision making related to medical diagnosis based on pairing function to compute similarity among medical cases. We have constructed an integrated computerized model which reflects a human diagnostician as computer model and through it; an integrated interaction between that model and the real human user (patient) is utilized for 1st stage diagnosis purposes.
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