国际医药卫生导报2016，Vol.22Issue(12)：1670-1673,4.DOI:10.3760/cma.j.issn.1007-1245.2016.12.002
人工神经网络及Logistic回归模型对预测体外冲击波治疗上尿路结石的疗效分析
Role of artificial neural network and logistic regression model in predicting effect of extracorporeal shock wave for upper urinary tract calculi
摘要
Abstract
Objective To explore the role of artificial neural network and logistic regression model in predicting the effect of extracorporeal shock wave for upper urinary tract calculi.Methods From January,2010 to January,2015,d 340 patients with renal calculus were treated by ESWL at our hospital.The predictive parameters were sex,symptoms induced by urethral irritation,blood urine,renal colic,stone position,stone of one side,age,BMI,disease course,and stone size.Artificial neural network and logistic regression model were built basing on these parameters to predict the clinical effect of ESWL for calculus of upper urinary tract.Results The most important five parameters in artificial neural network were stone size,disease course,blood urine,stone position,and BMI,with statistical differences (P＜0.05).The most important parameters in logistic regression model were disease course,blood urine,and stone position,with statistical differences (P＜0.05).Conclusions Artificial neural network and logistic regression model in predicting the effect of extracorporeal shock wave for upper urinary tract calculi are both highly accurate,so both are worth being clinically generalized.关键词
人工神经网络/Logistic回归模型/体外冲击波/上尿路结石Key words
Artificial neural network/Logistic regression model/Upper urinary tract calculi/Extracorporeal shock wave引用本文复制引用
蒋杰宏,姚聪,陈健芬,徐乐..人工神经网络及Logistic回归模型对预测体外冲击波治疗上尿路结石的疗效分析[J].国际医药卫生导报,2016,22(12):1670-1673,4.基金项目
广东省科技计划项目(2012201)Project of Scientific and Technological Plan in Guangdong (2012201) （2012201）
