Healthcare Expert System Based on Fuzzy Logic: Case Study on Diagnosing Headache
سال انتشار: 1397
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 709
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICISE04_012
تاریخ نمایه سازی: 1 دی 1397
چکیده مقاله:
Expert systems in healthcare are widely studied by researchers where the accuracy on diagnosing and efficiency of the system are the considerations also; expert systems have been playing an important role in serving and advancing healthcare and can play a vital role in such cases where the medical expert is not readily available. The purpose of this paper is to distinguish and diagnosis common headaches by fuzzy logic and fuzzy system. A fuzzy expert system for the distinguish types of common headaches is presented, that mamdani model was used in fuzzy inference engine using Max-Min as OR-AND operators and Centroid method was used as defuzzification technique. The fuzzy system was evaluated using data obtained from 150 patients and showed 82% good agreement and high ability in terms of correct diagnosis. Accuracy, Precision, sensitivity, specificity of the system were 86%, 93%, 85%, 88% for migraine , 93%, 91%, 55%, 99% for tension, 97%, 86%, 66%, 99% for headaches result of infection and 95%, 85%, 88%, 97% for headaches result of increase of ICP, respectively. To measure agreement of system results with the physician diagnosis, Kappa statistics was employed and showed a high relation,71% ,65%,74% and 84% for migraine, tension, headaches result of infection and headaches result of increase of ICP, respectively. According to proximity of common headaches symptoms, and importance of early diagnosis of headache, and favorable results of the implementation and evaluation of the suggested expert system, therefor this system can be very useful for diagnosis of common headaches with similar symptoms.
کلیدواژه ها:
نویسندگان
Monire Khayamnia
Ph.D. candidate of Applied Mathematics, Tehran Payame Noor University, Tehran, Iran
Mohammadreza Yazdchi
Associate Professor, Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
Mohsen Foroughipour
Associate Professor, Neurology school of medicine, Mashhad University of Medical Sciences, Mashhad, Iran