Application of Risk Assessment Model for Breast Cancer

Huaizhou Yang, Tian Luo, Chenzhuo Liu
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Abstract

Looking for a risk assessment model is of great significance for predicting, preventing and diagnosing breast cancer. This paper collects relevant data from SEER database(Survey, Epidemiology, and End Results), uses SVM (Support Vector Machine) and random forest in data mining to predict the possibility of breast cancer, and discusses the application value of Gail breast cancer risk assessment model. Finally, the prediction results based on three risk assessment models are analyzed. The analysis results show that the prediction accuracy rate of Gail model is more excellent.
乳腺癌风险评估模型的应用
寻找乳腺癌的风险评估模型对乳腺癌的预测、预防和诊断具有重要意义。本文从SEER数据库(Survey, Epidemiology, and End Results)中收集相关数据,利用数据挖掘中的SVM(支持向量机)和随机森林对乳腺癌的可能性进行预测,并探讨Gail乳腺癌风险评估模型的应用价值。最后,对基于三种风险评估模型的预测结果进行了分析。分析结果表明,Gail模型的预测准确率更高。
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