Decision making on medical diagnosis based on subjective and objective fuzzy aggregation functions alignment

Medical Diagnosis system engineering needs to be robust and realizable decision making system. Attributes related to medical decision making is crucial aspect in medical applications. However, these attributes are a mixture of linguistic values and fuzzy intervals. Also, there are Fuzzy relations that are used in description of Symptoms. Fuzzy set and fuzzy relations are used to represent medical knowledge as network of symptoms and diseases connected with each other by logical relations. Like high temperature is related to fever diagnosis. For example each object in the domain knowledge has n scores reflecting the symptoms, one for each m attribute. For example a symptoms (object) has an attribute from physical set properties, (e.g., high temperature), and other attributes set is from mental set properties (e.g., stress high). Then for each attribute there is assorted list that list each symptoms with its attribute sorted by scores (fuzzy values). This can be evaluated and reasoned using monotone aggregation function or combining rules. This is because the decision making is aggregated on different ontologies that are using different knowledge layers to select the optimal alternatives due to selected criteria that have aggregation operators. These aggregation operators are used to model medical mental view and physical view in our model.