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Medical image diagnosis of lung cancer by hybrid multi-layered GMDH-type neural network using knowledge base

机译:使用知识库的混合多层GMDH型神经网络的肺癌医学图像诊断

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A revised Group Method of Data Handling (GMDH)-type neural network algorithm for medical image diagnosis is proposed, and is applied to medical image diagnosis of lung cancer. In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis, and the revised GMDH-type neural network algorithm can identify the characteristics of the medical images accurately. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS), and it is shown that the revised GMDH-type neural network can be easily applied to the medical image diagnosis.
机译:提出了一种修订的数据处理组(GMDH)型医学图像诊断的神经网络算法,并应用于肺癌的医学图像诊断。 在该算法中,医学图像诊断的知识库用于组织用于医学图像诊断的神经网络架构,并且修正的GMDH型神经网络算法可以精确地识别医学图像的特性。 拟合医学图像的复杂性的最佳神经网络架构被自动组织,以便最小化定义为平方(PSS)预测和定义的预测误差标准,并且示出了修订的GMDH型神经网络可以容易地应用于 医学图像诊断。

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