Fuzzy Rule-Based Expert System for Assessment Severity of Asthma
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Prescription medicine for asthma at primary stages is based on asthma severity level. Despite major progress in discovering various variables affecting asthma severity levels, disregarding some of these variables by physicians, variables’ inherent uncertainty, and assigning patients to limited categories of decision making are the major causes of underestimating asthma severity, and as a result low quality of life in asthmatic patients. In this paper, we provide a solution of intelligence fuzzy system for this problem. Inputs of this system are organized in five modules of respiratory symptoms, bronchial obstruction, asthma instability, quality of life, and asthma severity. Output of this system is degree of asthma severity in score (0–10). Evaluating performance of this system by 28 asthmatic patients reinforces that the system’s results not only correspond with evaluations of physicians, but represent the slight differences of asthmatic patients placed in specific category introduced by guidelines.
KeywordsAsthma Severity Assessment Fuzzy Expert system
I would like to appreciate all who gave me the possibility to complete this paper. I want to thank the physicians and staff of Immunology, Asthma & Allergy Research center for their collaboration in providing necessary knowledge. I thank Dr Heydarnejad and Dr. Fazlollahi for their guidance, Mehdi Taherian for contribution in knowledge representation I appreciate Zahra Zolnoor, Ali Zolnoor, and Mohammad Reza Zolnoor for providing general information. Finally I thank Neda Kharghani for reviewing this paper and providing useful comments.
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