Research on hepatitis auxiliary diagnosis model based on fuzzy integral and GA — BP neural network

In this paper, in order to improve the accuracy of hepatitis diagnosis in computer-aided diagnosis system, the medical data from the network public database were optimized by GA-BP neural network algorithm, and then we obtained the important index of judging the hepatitis and the weight of the index through this algorithm, we regarded the weight as the single point measure of non-additive, and then using the fuzzy integral calculated the probability of a person being diagnosed with hepatitis. From the results of calculation, using fuzzy integral can greatly improve the accuracy of hepatitis auxiliary diagnosis.