Objective:To predict the postoperative risk of patients with colorectal cancer based on support vector machine（SVM）.Methods:Clinical data of 199 patients with colorectal cancer were collected retrospectively from the hospital from January2011 to December 2013

and patients were divided into two groups according to disease free survival or not. Basic statistics analysis and logistic regression were conducted by SAS9.2. Parameters optimization and establishment of SVM model wereanalyzed by R3.2.4. Receiver operating characteristic curve（ROC）and area under the curve（AUC）were used to evaluate their performance. Results:Differences analysis showed that total protein

albumin

positive lymph node number

tissue type

N

p53

radiotherapy and chemo-therapy were significantly different between prognosis groups（P<0.05）. Multiple logistic regression showed that N2（OR=13.5

95%CI=3.85 to 47.5）

p53 positive（OR=0.314

95%CI=0.125 to 0.790）maybe the risk factors of prognosis. The prediction accuracy of linear-kernel

polynomial-kernel

sigmoid-kernel and RBF（radial basis function）-kernel was 69.70%

66.70%

69.70%

74.24%

respectively. The results of performance comparison showed that SVM models performed better than logistic regression model;RBF-SVM was the best among all the models

with the prediction accuracy of 74.24%;sensitivity

specificity and AUC were 0.714

0.765

0.708（95%CI=0.551 to 0.866）

respectively. Conclusion:N2 staging and p53 positive maybe the risk factors for prognosis and more attention should be paid to decrease the risk of prognosis.