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Research on Hepatitis Auxiliary Diagnosis Model Based on Fuzzy Integral and GA - BP Neural Network

机译:基于模糊积分和GA - BP神经网络的肝炎辅助诊断模型研究

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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.
机译:在本文中,为了提高计算机辅助诊断系统中肝炎诊断的准确性,通过GA-BP神经网络算法优化了来自网络公共数据库的医疗数据,然后我们获得了判断肝炎的重要指标通过该算法的索引的重量,我们认为重量作为非添加剂的单点测量,然后使用模糊积分计算患有肝炎的人的可能性。从计算结果来看,使用模糊积分可以大大提高肝炎辅助诊断的准确性。

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