Hybrid Prediction Model Based on BP Neural Network for Lung Cancer

摘要：

Recent researches show that lung cancer owns actual close-response relationship with calendar-year smoking environment exposure matrix and individual medical record. In this paper, two hybrid prediction models based on BP neural network, ES (exponential smoothing) and FCM (Fuzzy C-Means) clustering are proposed to predict the possible rate and ages of smokers suffering the lung cancer.The BP-ES (Exponential Smoothing) model can exert the superiorities of the time series datum of smoking crowds and other pathogenic factors; and the BP-FCM clustering model can reduce the parameter amount and complexity of BP nets training greatly.The experiments show that the accuracy of the hybrid models are enhanced greatly contrasted with single BP neural network, and can work as effective methods for the statistic, analysis and prediction to lung cancer.

作者: Aobing Sun Yubo Tan Dexian Zhang

作者单位: School of Information Science and Engineering,Henan University of Technology Zhengzhou,450001,China

会议类型: 国际会议

会议名称: 2008 IEEE International Symposium on IT in Medicine and Education(2008信息技术在医学和教育中的应用国际研讨会)(ITME 2008)

会议地点: 厦门

会议语种:英文

页码: 532-535

在线出版日期: 2008-12-12（万方平台首次上网日期，不代表论文的发表时间）