矽肺病人发元素谱的Q型逐次信息群分  

Q-TYPE STEPWISE INFORMATIONAL CLUSTER ANALYSIS FOR THE ELEMENTS TABLE OF SILICOTICS

作　　者：李丙瑞[1] 蒋士琦 许树贞 申敬贤 

机构地区：[1]兰州大学化学系,兰州730000 [2]白银公司劳动卫生研究所,白银730900

出　　处：《计算机与应用化学》1995年第4期285-288,共4页Computers and Applied Chemistry

基　　金：甘肃省自然科学基金资助项目

摘　　要：用Q型逐次信息群分对白银矿区42名矽肺患者和41名正常人头发样的元素谱Cr、Zn、Mg、Al、Cd进行无监督模式识别,获得分类清晰的谱系图,83个样本的判别正确率达98.8％。这一结果表明,元素谱的Q型逐次信息群分可望成为研究和预测矽肺病的一种新技术。Unsupervised pattern recognition for the elements table, Cr,Zn,Mg,Al,Cd, in the hair species of the 42 silicotics and the 41 others in Baiyin diggings has been performed with Q-typestepwise informational cluster analysis and clearly classified dendrograms has been given out, in which, the accuracy is 98.8%. The results indicate that Q-type stepwise informational cluster analysis for the microelements table may be used as a new technique to research and predict anthrasilicosis.

关 键 词：聚类分析 模式识别 矽肺 元素谱 人发 

分 类 号：R135.2[医药卫生—劳动卫生]