摘要
应用火焰原子吸收法和石墨炉原子吸收法测定了冠心病患者和对照组（健康人）血清中Ｚｎ、Ｃｕ、Ｆｅ、Ｃａ、Ｍｇ、Ｃｒ、Ｍｎ和Ｓｒ等的含量。对所得数据用反向传播神经网络（Ｂ－Ｐ法）进行分析，建立了冠心病的神经网络识别系统，预报识别率达１００％，可作为该病诊断的一种有效的辅助手段。
The methods of FAAS and GFAAS were applied to determine the contents of Zn,Cu,Fe,
Ca,Mg,Cr,Mn and Sr in serum of coronary disease patients and healthy people.The data from
these methods were analysed by backpropagation algorithm for neural network and an
identification system of was established .The recoveries are 100% for the prediction set of
samples and it can be an efficient aid to diagnose this kind of disease.
出处
《分析试验室》
CAS
CSCD
1999年第2期42-43,共2页
Chinese Journal of Analysis Laboratory
