Designing a Disease Diagnosis System by Using Fuzzy Set Theory
Proceedings of the 5 Asian Mathematical Conference, Malaysia 2009
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DESIGNING A DISEASE DIAGNOSIS SYSTEM BY USING FUZZY SET THEORY Ahmad Mahir R., Asaad A. Mahdi and Ali A. Salih
School of Mathematical Sciences, Faculty of Science and Technology Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, MALAYSIA E-mail: mahir@ukm.my ; wakilali@yahoo.com ; asaadmahdi@gmail.com Abstract: Many diseases affecting millions of people every day. Information technology could be used to reduce the mortality rate and waiting time to see the specialist. As clinical decision making inherently requires reasoning under uncertainty, expert systems, fuzzy set theory and fuzzy logic are a highly suitable basis for developing knowledge based systems in medicine for tasks such as diagnosis of diseases, the optimal selection of medical treatments, and for real time monitoring of patient data. Our goal is to develop a methodology using fuzzy set theory to assist general practitioner in diagnosing and predicting patients condition from certain “ rules based on experience ”. Medical practitioner other than specialists may not have enough expertise or experience to deal with certain high risk diseases. With this system the patients with high risk factors or symptoms could be short listed to see the specialists for further treatment. The intuition is based on doctors ability to make initial judgment based on his study and experience . In this paper we designed a questionnaire to collect the data needed. We chose a random sample of 170 patient from clinics and hospitals. The questionnaire depends on three different sets . The first set is the diseases symptoms set, which contain information on symptoms of diseases such as fever, high temperature, headache, rash, vomiting, etc.. The second set is the diseases set ( chicken pox, Hepatitis B, etc.),and finally the patients set ( a sample of 49 patients), the next step was to form the membership functions for each symptom, and then the
th
DESIGNING A DISEASE DIAGNOSIS SYSTEM BY USING FUZZY SET THEORY Ahmad Mahir R., Asaad A. Mahdi and Ali A. Salih
School of Mathematical Sciences, Faculty of Science and Technology Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, MALAYSIA E-mail: mahir@ukm.my ; wakilali@yahoo.com ; asaadmahdi@gmail.com Abstract: Many diseases affecting millions of people every day. Information technology could be used to reduce the mortality rate and waiting time to see the specialist. As clinical decision making inherently requires reasoning under uncertainty, expert systems, fuzzy set theory and fuzzy logic are a highly suitable basis for developing knowledge based systems in medicine for tasks such as diagnosis of diseases, the optimal selection of medical treatments, and for real time monitoring of patient data. Our goal is to develop a methodology using fuzzy set theory to assist general practitioner in diagnosing and predicting patients condition from certain “ rules based on experience ”. Medical practitioner other than specialists may not have enough expertise or experience to deal with certain high risk diseases. With this system the patients with high risk factors or symptoms could be short listed to see the specialists for further treatment. The intuition is based on doctors ability to make initial judgment based on his study and experience . In this paper we designed a questionnaire to collect the data needed. We chose a random sample of 170 patient from clinics and hospitals. The questionnaire depends on three different sets . The first set is the diseases symptoms set, which contain information on symptoms of diseases such as fever, high temperature, headache, rash, vomiting, etc.. The second set is the diseases set ( chicken pox, Hepatitis B, etc.),and finally the patients set ( a sample of 49 patients), the next step was to form the membership functions for each symptom, and then the
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