Predicting Five-year Overall Survival in Patients with Non-small Cell Lung Cancer by ReliefF Algorithm and Random Forests

摘要：

　　Non-small Cell Lung Cancer(NSCLC)is a leading death disease in many countries.Many studies are focusing on exact surgical approaches to treat the disease.The five-year overall survival rate for NSCLC patients is typically predicted by traditional regression models with small samples and data size.In this paper,we introduce machine learning tools with feature selection algorithms and random forests classifier to predict the five-year overall survival rate based on a large database.The results of this experiment show that our proposed framework is better than other machine learning approaches to predict the five-year overall survival rate.

关键词： ReliefF Algorithm Feature Selection Five-year Overall Survival Non-small Cell Lung Cancer (NSCLC) Random Forests

作者: Xueyan Mei

作者单位: School of Professional Studies Columbia University New York City,USA

会议类型: 国际会议

会议名称: 2017 IEEE 2nd Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2017)(2017 IEEE 第2届先进信息技术、电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 2527-2530

在线出版日期: 2017-03-25（万方平台首次上网日期，不代表论文的发表时间）