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首页> 外文期刊>International Journal of Physical Sciences >Automatic disease diagnosis systems using pattern recognition based genetic algorithm and neural networks
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Automatic disease diagnosis systems using pattern recognition based genetic algorithm and neural networks

机译：基于模式识别的遗传算法和神经网络的疾病自动诊断系统

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This paper presented three disease diagnosis systems using pattern recognition based on genetic algorithm (GA) and neural networks. All systems dealt with feature selection and classification. GA chose subsets of features for the input of the classifier (neural network) and the accuracy of the classifier determined the percentage of effectiveness of each subset of features. The classifiers using in this paper were general regression neural network (GRNN), radial basis function (RBF) and radial basis network exact fit (RBEF). It uses breast cancer and hepatitis disease datasets taken from UCI machine learning database as medical dataset. The system performances were estimated by classification accuracy and they were compared with similar methods without feature selection.
机译：本文提出了三种基于模式识别的遗传算法和基于神经网络的疾病诊断系统。所有系统都处理功能选择和分类。 GA选择了特征子集作为分类器（神经网络）的输入，分类器的准确性决定了每个特征子集的有效性百分比。本文使用的分类器是通用回归神经网络（GRNN），径向基函数（RBF）和径向基网络精确拟合（RBEF）。它使用从UCI机器学习数据库中获取的乳腺癌和肝炎疾病数据集作为医学数据集。通过分类精度评估系统性能，并与没有特征选择的类似方法进行比较。

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