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Medical diagnosis process involves many levels and considerable amount oftime and money are invariably spent for the first level of diagnosis usuallymade by the physician for all the patients every time. Hence there is a needfor a computer based system which not only asks relevant questions to thepatients but also aids the physician by giving a set of possible diseases fromthe symptoms obtained using logic at inference. In this work, an ICD10 basedMedical Expert System that provides advice, information and recommendation tothe physician using fuzzy temporal logic. The knowledge base used in thissystem consists of facts of symptoms and rules on diseases. It also providesfuzzy severity scale and weight factor for symptom and disease and can varywith respect to time. The system generates the possible disease conditionsbased on modified Euclidean metric using Elders algorithm for effectiveclustering. The minimum similarity value is used as the decision parameter toidentify a disease.

ICD 10 Based Medical Expert System Using Fuzzy Temporal Logic