A Fuzzy Rule-Based Expert System for Diagnosing Asthma

作者：Zarandi M H Fazel^*; Zolnoori M; Moin M; Heidarnejad H

来源：Scientia Iranica, 2010, 17(2): 129-142.

• Fuzzy sets
• Medical expert system
• Asthma
• Diagnosis

Asthma is a chronic lung disorder of which the number of sufferers estimated to be between 1.4-27.1% of the population in different areas of the world. 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 fuzzy rule-based expert system. to alleviate this hazard by diagnosing asthma at initial stages. A knowledge representation of this system is provided from, a high level, based on patient perception, and organized into two different structures called Type A and Type B. Type A is composed of six modules, including symptoms, allergic rhinitis, genetic factors, symptom hyper-responsiveness, medical factors and environmental factors. Type B is composed of 8 modules including symptoms, allergic rhinitis, genetic factors, response to short-term drug use, bronchodilator tests, challenge tests, PEF tests and exhaled nitric oxide. ?he final result of every system is de-fuzzified in order to provide the assessment of the possibility of asthma for the patient. Verification and validations criteria are considered throughout a life-cycle; the system was developed by the participation of general physicians, experienced asthma physicians and asthmatic patients.

• 出版日期2010-12