CAJ | 학술논문

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。
이용판별분석방법통과대측량적12개아이자해묵씨증(Alzheimer’s disease, AD)환자화12개건강자적뇨액양본중인다분알（Catecholamines, CA）함량적측정급농도작위훈련집건립판별함수，진행질병적진단，교차험증착오솔위4.2%。채용수궤여하적4개수거대입판별함수，진행예측，결과표명구유흔호적예측능력，정학솔체도료100%。차방법가이통과측량인체뇨액중CA 함량측정급농도래진단 AD ，대 AD 적진조검측화조기치료비상중요。2조선성판별함수분별위-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。
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.