基于支持向量机的乳腺癌化疗预后状态预测

Prediction of prognosis for breast cancer based on support vector machine

乳腺癌是危害女性生命的一种恶性肿瘤。目前,在乳腺癌治疗方面,新辅助化疗获得了良好的成果,使众多女性恢复了健康。支持向量机在实际应用中有着良好的泛化和学习能力,并在商业、经济以及医疗等领域有所应用。采用决策树分类器和支持向量机分类器,结合乳腺癌新辅助化疗随访记录数据,预测乳腺癌患者新辅助化疗的预后状态,实验结果表明使用支持向量机的效果好于使用决策树的效果,在支持向量机中使用径向基核函数时获得了最高的准确率,达到了84.08%,由此可见,该分类方法可能成为一种乳腺癌新辅助化疗的预后状态的有效预测工具。

Mammary cancer is a malignant tumor of the harm of women＇s life. At present, in the treatment of mammary cancer, neo-adjuvant chemotherapy achieved good results, so that many women back to health. Support vector machine has a good generalization and learning ability in practical application, and has been applied in the commercial, economic, medical and other fields. According to Neo-adjuvant chemotherapy in mammary cancer follow-up record data, using decision tree classifier and SVM classifier, predict the prognosis of neo-adjuvant chemotherapy for mammary cancer patients, the experimental results show that the use of support vector machine is better than the effect of using decision tree, using RBF kernel function in support vector machines have the highest accuracy, reached 84.08% o Thus, the classification method, may be an effective tool to predict prognosis for mammary cancer neo-adjuvant chemotherapy.