摘要
为解决现有一般方法难以甚至无法辨识生化测量仪输出数据与样品中多种特定物质含量之间的非线性多元复杂函数关系这一难题,研究了运用人工神经网络处理生化测量数据如光谱扫描数据的新方法,使得在既不增加其它设备,也不对现有仪器及其测量方法作任何改动的情况下能够大量增加生化测量仪器的检测项目。以对胆固醇含量检测为例的仿真结果表明该方法是有效的。该方法不但简便易行,而且能高效快捷地批量处理测量数据。
It is difficult to recognize the complicated non-linear multi-variable function relationship between biochemistry testing readout and the content of specific substances in the sample with traditional approaches. A new approach applying neutral network is introduced in the article to handle such biochemistry testing statistics as those in spectrum scan. The approach requires no additional apparatus to present equipments. No modification is needed in present testing equipment or testing approaches, either. Whereas, present testing equipment is available for more biochemistry testing projects if this introduced approach is adopted. An example which simulated the testing for the content of cholesterol has proved the validity of the approach, which is easy to carry out and can process a series of testing statistics.
出处
《中国生物医学工程学报》
CAS
CSCD
北大核心
2007年第2期161-165,共5页
Chinese Journal of Biomedical Engineering
基金
湖南省自然科学基金项目(04JJ40044)
湖南省教育厅科研基金项目(06C603)
关键词
神经网络
医学检验
生化测量
光谱扫描
neutral network
medical examination
biochemistry measurement
spectrum scan
