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Fuzzy neural network applications in medicine

机译:模糊神经网络在医学中的应用

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摘要

A fuzzy neural network based approach to 3-D heart motion understanding is proposed. Knowledge from cardiologists is used to specify different classes of motion and classification rules. The objective of this approach is to find the decisions for all possible classes of motion in the form of possibilities. The neural networks in the motion understanding system are independent of each other in operation and are cascaded to form a tree structure where each terminal node represents one possible class and each nonterminal node composed of a neural network represents one classification rule. In each network, the propagation rule is described by a fuzzy function and a supervised learning method is employed to train the parameters representing the type of fuzzy logic operation among inputs and the weights between each input and output neurons. Decision values can be computed by applying fuzzy reasoning technique to the outputs of the networks. Experiments on real data have been conducted to corroborate the proposed techniques.
机译:提出了一种基于模糊神经网络的3-D心脏运动理解方法。来自心脏病专家的知识用于指定不同类别的运动和分类规则。这种方法的目的是以可能性的形式为所有可能的运动类别找到决策。运动理解系统中的神经网络在操作上彼此独立,并级联形成一个树形结构,其中每个终端节点代表一个可能的类别,每个由神经网络组成的非终端节点代表一个分类规则。在每个网络中,传播规则由模糊函数描述,监督学习方法用于训练代表输入之间的模糊逻辑运算类型以及每个输入和输出神经元之间权重的参数。可以通过将模糊推理技术应用于网络的输出来计算决策值。已经对真实数据进行了实验,以证实所提出的技术。

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