高等学校化学学报 ›› 1998, Vol. 19 ›› Issue (4): 530.

• 论文 • 上一篇    下一篇

人工神经网络方法用于肺癌的辅助诊断

张卓勇1, 刘思东1, 丁保军1, 任玉林2, 陈杭亭3, 曾宪津3   

  1. 1. 东北师范大学化学系, 长春, 130024;
    2. 吉林大学化学系, 长春, 130023;
    3. 中国科学院长春应用化学研究所, 长春, 130022
  • 收稿日期:1997-04-11 出版日期:1998-04-24 发布日期:1998-04-24
  • 通讯作者: 张卓勇,男,41岁,博士,副教授.
  • 作者简介:张卓勇,男,41岁,博士,副教授.
  • 基金资助:

    国家自然科学基金;国家教委优秀年轻教师基金

Artificial Neural Network Applied to Diagnosis of Lung Cancer

ZHANG Zhuo-Yong1, LIU Si-Dong1, DING Bao-Jun1, REN Yu-Lin2, CHEN Hang-Ting3, ZENG Xian-Jin3   

  1. 1. Department of Chemistry, Northeast Normal University, Changchun, 130024;
    2. Department of Chemistry, Jilin University, Changchun, 130023;
    3. Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022
  • Received:1997-04-11 Online:1998-04-24 Published:1998-04-24

摘要: 根据人发和血清中微量元素的含量,将人工神经网络(ANN)用于正常人与癌症患者的分类预测.用独立预测样本作了检验,表明该方法可作为肺癌诊断的一种辅助手段.讨论了当预测样本中有元素缺损时ANN的分类预测情况,并研究了人发和血清样品中的元素对分类预测的影响.

关键词: 人工神经网络, 分类, 微量元素, 人发, 血清

Abstract: Artificial neural network(ANN) approach was applied to classification of normal persons and lung cancer patients based on the metal content of hair and serum samples obtained by inductively coupled plasma atomic emission spectrometry(ICP-AES) for the two groups. This method was verified with independent prediction samples and can be used as an aiding means of the diagnosis of lung cancer. The case of predictive classification with one element missing in the prediction samples was studied in details. The significance of elements in hair and serum samples for classification prediction was also investigated.

Key words: Artificial neural network, Classification, Trace element, Hair, Serum

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