Diagnosis Blood Test for Liver Disease using Fuzzy Logic

Most commonly lab test used to measure or monitor general health and liver health are following: Liver Biochemical/Function test, CBC and Chemistry Panel. In this thesis we are focusing on CBC. Complete Blood Counts measure the four components of blood leukocytes, Hematocrit, Hemoglobin and Blood Platelets. For this purpose we design fuzzy control model which help to diagnose a disease related to human liver. Fuzzy design model have four input variables (leukocytes, hematocrit, hemoglobin, blood platelets) and three output variables (infection fight, anemia and thrombocytopenia). Fuzzy design model algorithm divided into four steps Fuzzification, Inference Engine, Rule selector and Defuzzification. Each input variable and output variable graphically represented by MF’s and regions. Fuzzifier takes the crisp values of four input variables [leukocytes, hematocrit, hemoglobin, blood platelets] and gives the eight linguistic variables as output. As input variables maps with the MF’s in two regions that’s why four input variables have eight linguistic variables. Fuzzy control model input variable are independent so we have minimum twelve rules. The output of fuzzifier becomes the input to inference engine. So inference engine takes eight input values from fuzzifier and use min max method (AND Operation) and output R value; Mamadani-min process is used for generating R values