01685nam a22001577a 4500999001700000100007400017245005800091260003000149300000900179500106300188700004101251856003201292942001101324952009001335952010201425  c65913d65910  aSabagi, Mubashreen a16MSIT25aSupervisor - Dr. Akbar Hussain Jalbani  aFuzzy Expert System for Diagnosing  Diabetes Mellitus  aNawabshah:bQUEST,c2019.  a33p.  aABSTRACT


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 %.
  aDepartment of Information Technology  uhttp://tinyurl.com/yc4aybyb  cTHESIS  00104070aRESEARCHbRESEARCHd2019-10-18l0pMP/55-696r2019-10-18 00:00:00yTHESIS  00104070aRESEARCHbRESEARCHd2023-12-21l0pMP/47-552r2023-12-21 00:00:00w2023-12-21yTHESIS