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Bayes判别分析在基于儿茶酚胺的阿尔茨海默病预测研究中的应用

Diagnosis of Alzheimer’s disease and its prediction basing on Bayes discriminant analysis method using Catecholamines data

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【Author】 Li Zuojing~(1,2),Li Qing~2,Ling Junhong~3 and Bi Kaishun~(2*) (1.School of Medical Devices,Shenyang Pharmaceutical University,Shenyang 110016,Liaoning,China) (2.School of Pharmacy,Shenyang Pharmaceutical University,Shenyang 110016,Liaoning,China) (3.School of Medicall Engineering,Shenyang Pharmaceutical University,Shenyang 110016,Liaoning,China)

【机构】沈阳药科大学医疗器械学院；沈阳药科大学药学院；沈阳药科大学制药工程学院；

【摘要】利用判别分析方法通过对测量的12个阿尔茨海默氏症(Alzheimer’s disease,AD)患者和12个健康者的尿液样本中儿茶酚胺(Catecholamines,CA)含量的测定及浓度作为训练集建立判别函数,进行疾病的诊断,交叉验证错误率为4.2%。采用随机余下的4个数据带入判别函数,进行预测,结果表明具有很好的预测能力,正确率达到了100%。此方法可以通过测量人体尿液中CA含量测定及浓度来诊断AD,对AD的尽早检测和早期治疗非常重要。2组线性判别函数分别为-19.91024+0.21873*E+0.23742*NE+0.11155*DOA+0.41789*L-DOPA-0.12661*DOPAC;-2.24864+0.03070*E+0.04914*NE+0 06892*DOA+0.01704*L-DOPA+0.01598*DOPAC。更多还原

【Abstract】 In this paper,discriminate analysis method was applied to diagnose the Alzheimer’s disease(AD) using the data of determination and concentration of the Catecholamines(CA) content in the urine samples.The measurement of 12 AD patients and 12 healthy individuals was applied to build the model as training set.The cross-validation error rate is 4.2%.The model has a good predictive ability with the correct rate of 100%.This method plays an important role for AD detection and early treatment through measuring CA content determination and concentration in human urine.The linear discriminate function was -19.91024+0.21873~*E+ 0.23742~*NE+ 0.11155~* DOA+0.41789~*L-DOPA-0.12661~*DOPAC,-2.24864+0.03070~*E+0.04914~*NE+0.06892~*DOA+0.01704~*L-DOPA+0.01598~*DOPAC.更多还原

【关键词】 Bayes判别分析；阿尔茨海默病(AD)；儿茶酚胺(CA)；生物标记物；
【Key words】 Bayesian discriminant analysis； Alzheimer’s disease(AD)； catecholamine(CA)； biomarkers；

【基金】国家自然科学基金资助项目(81102784/H2803)

【文献出处】计算机与应用化学 ,Computers and Applied Chemistry , 编辑部邮箱 ,2013年05期

【分类号】R749.16
【被引频次】4
【下载频次】141

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