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双向联想记忆神经网络及其在肺癌患者分类判别中的应用
Bidirectional Associative Memory and Its Application to Classification of Lung Cancer Patients
【摘要】 给出双向联想记忆 (BAM)神经网络的基本原理。在此基础上 ,根据血清中微量元素的含量 ,将双向联想记忆神经网络用于正常人与肺癌患者的分类判别。实验结果表明 :用独立预测样本作检验 ,在本工作所选定的条件下 ,可以达到 10 0 %的正确识别率。并讨论了双向联想记忆神经网络的影响因素。
【Abstract】 The basic theory of bidirectional associative memory (BAM) was given and the BAM approach was applied to the classification of normal people and lung cancer patients based on the microelement contents in serum samples.This method was verified with independent prediction samples and can discriminate all lung cancer patients at rate of 100 percent under certain conditions.The results obtained by BAM are slightly better than those obtained by back propagation neural network (97%).Results showed that the BAM could be a promising aiding method for diagnosis of lung cancer.The effects of network parameters were investigated and related problems were discussed.
【Key words】 Bidirectional associative memory; Artificial neural network; Classification; Microelement; Serum; Lung cancer;
- 【文献出处】 光谱学与光谱分析 ,Spectroscopy and Spectral Analysis , 编辑部邮箱 ,2002年02期
- 【分类号】R734.2
- 【被引频次】8
- 【下载频次】118