A Type-II Fuzzy Expert System For diagnosis of Asthma

Asthma is a chronic lung disorder of which the number of sufferers estimated to be 10% of the population in Iran. Results of various studies show that asthma is usually under-diagnosed, especially in developing countries, because of limited access to medical specialist and laboratory data. The purpose of this paper is to design a Type-II fuzzy rule-based expert system to alleviate this hazard by diagnosing asthma at initial stages. Rule-base of this system is acquired from aggregation of patients’ data and knowledge of experts. Results show that combination of these two methods can enhance the diagnosis capability of expert system. Type-II fuzzy technique is used to handle the uncertainty in this system and improve the accuracy of diagnosis.