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Multiperspective recognition applied to the computer-aided medical diagnosis-a comparative study of methods

机译:应用对计算机辅助医学诊断的多级识别 - 一种方法对比研究

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This paper deals with the multiperspective recognition technique applied to the computer-aided decisions in medicine. For three different concepts of multiperspective classification, i.e. direct, decomposed independent and decomposed dependent approach, several decision algorithms are presented. They are: probabilistic (empirical Bayes) algorithm, nearest neighbour algorithm, fuzzy method and artificial neural network of the back propagation and counter propagation types. Proposed methods and algorithms have been applied to the computer-aided diagnosis of chronic renal failure and decisions in non-Hodgkin lymphoma. Results of experimental investigations on the real data and outcomes of the comparative analysis of discussed algorithms are presented.
机译:本文涉及应用于医学计算机辅助决策的多级识别技术。对于三种不同的多次分类概念,即直接,分解独立和分解的依赖方法,呈现了几种决策算法。它们是:概率(经验贝叶斯)算法,最近邻算法,模糊方法和后传播的模糊方法和人工神经网络。提出的方法和算法已应用于计算机辅助诊断慢性肾功能衰竭和非霍奇金淋巴瘤的决定。介绍了对讨论算法比较分析的实验研究结果。

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