Fuzzy Expert System for Diagnosing Diabetes Mellitus
By: Sabagi, Mubashreen 16MSIT25 Supervisor - Dr. Akbar Hussain Jalbani.
Contributor(s): Department of Information Technology.
Material type:
BookPublisher: Nawabshah: QUEST, 2019Description: 33p.Online resources: Click here to access online
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Thesis and Dissertation
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Research Section | Available | MP/47-552 | |||
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Thesis and Dissertation
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Research Section | Available | MP/55-696 |
ABSTRACT
Diabetes is a dangerous disease in which the human body cannot produce proper quantity of insulin. Diabetes will also develop heart disease, kidney disease, blindness, nerve damage, and blood vessel damage. This research uses Mamdani type expert systems for a diabetes diagnosis. Fuzzy expert system is a group of membership functions and rules. Fuzzy based expert systems are leaning toward numerical computing.
In which diagnose the diabetes using four different type of input age, gender and two blood test HbA1c and FPG using MATLAB Fuzzy Logic Designer in which first create fuzzy sets through fuzzification and fuzzy inference engine create the rules and facts and apply the rules on those facts to take the appropriate decision on the basis of given information that person is affected by diabetes or not and provides the description of result. Finally defuzzification method is used to convert the fuzzy output set into a crisp output. The output of the proposed fuzzy inference system is encouraging and provides the accuracy of 81.2 %.
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