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首页> 外文期刊>Expert systems with applications >Computer aided medical diagnosis system based on principal component analysis and artificial immune recognition system classifier algorithm
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Computer aided medical diagnosis system based on principal component analysis and artificial immune recognition system classifier algorithm

机译：基于主成分分析和人工免疫识别系统分类器算法的计算机辅助医学诊断系统

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摘要

In this study, diagnosis of lung cancer, which is a very common and important disease, was conducted with computer aided medical diagnosis system based on principal component analysis and artificial immune recognition system. The approach system has two stages. In the first stage, dimension of lung cancer dataset that has 57 features is reduced to 4 features using principal component analysis. In the second stage, artificial immune recognition system (AIRS) was our used classifier. We took the lung cancer dataset used in our study from the UCI (from University of California, Department of Information and Computer Science) Machine Learning Database. The obtained classification accuracy of our system was 100% and it was very promising with regard to the other classification applications in literature for this problem.
机译：在这项研究中，通过基于主成分分析和人工免疫识别系统的计算机辅助医学诊断系统，对肺癌这一非常常见和重要的疾病进行了诊断。进场系统有两个阶段。在第一阶段，使用主成分分析将具有57个特征的肺癌数据集的维数减少为4个特征。在第二阶段，人工免疫识别系统（AIRS）是我们使用的分类器。我们从UCI（加利福尼亚大学信息与计算机科学系）机器学习数据库中提取了用于研究的肺癌数据集。我们系统获得的分类精度为100％，对于该问题在文献中的其他分类应用方面非常有希望。

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