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Medical Application Of Information Gain Based Artificial Immune Recognition System (airs): Diagnosis Of Thyroid Disease

机译:基于信息增益的人工免疫识别系统(空气)的医学应用:甲状腺疾病的诊断

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In this paper, we have made medical application of a new artificial immune system named the information gain based artificial immune recognition system (IG-AIRS) which minimizes the negative effects of taking into account all attributes in calculating Euclidean distance in shape-space representation which is used in many artificial immune systems. For medical data, thyroid disease data set was applied in the performance analysis of our proposed system. Our proposed system reached 95.90% classification accuracy with 10-fold CV method. This result ensured that IG-AIRS would be helpful in diagnosing thyroid function based on laboratory tests, and would open the way to various ill diagnoses support by using the recent clinical examination data, and we are actually in progress.
机译:在本文中,我们已经在医学上应用了一种新的人工免疫系统,即基于信息增益的人工免疫识别系统(IG-AIRS),该系统可最大程度地减少在形状空间表示中计算欧几里德距离时考虑所有属性的负面影响。用于许多人工免疫系统。对于医学数据,将甲状腺疾病数据集应用于我们提出的系统的性能分析。我们提出的系统使用10倍CV方法达到了95.90%的分类精度。该结果确保了IG-AIRS将有助于根据实验室测试诊断甲状腺功能,并通过使用最新的临床检查数据为各种疾病的诊断支持开辟道路,并且我们实际上正在进行中。

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