支持向量机在临床疾病诊断中的应用

The Use of SVM in the Clinical Disease Diagnosis

基于支持向量机的最优二分类方法,以癌症诊断为例,构建了疾病诊断的支持向量机模型.对50例非癌症患者和100例癌症患者的腺苷三磷酸酶(ATP酶)和琥珀酸脱氢酶(SDH酶)活性两项指标分组进行训练和仿真诊断,检测样本的诊断正确率为98.03%,故可以用支持向量机建立临床疾病诊断系统.

Take cancer diagnosis for example, a clinical disease diagnosis model based on Support Vector Machine Optimal Classifier can be gained. Then, the values of adenosine triphosphatase （ATPase） and succinate dehydrogenase （SDHase） of 50 healthy people and 100 cancer patients are divided into groups to be trained and simulated. The correct diagnosis rate of the samples is up to 98. 03%, which indicates that Support Vector Machine can be used to set up clinical disease diagnosis system.