会议专题

The Risk Prediction of Type 2 Diabetes based on XGBoost

  This paper applies the XGBoost method to construct a predictive model for the risk of type 2 diabetes which based on the physical examination data.The paper takes the real physical examination records of the same batch of people in a health check-up center from 2010 to 2015 as the data source,and evaluates the feature importance.Finally,28 characteristic variables are selected as the model input,and a phase is obtained.Compared with other common classification algorithms,the prediction model with higher prediction accuracy and stronger generalization ability has certain clinical reference value for the risk prediction of type 2 diabetes.

XGBoost type 2 diabetes risk prediction

Wei Ji Shaofu Lin

Faculty of Information Technology,Beijing University of Technology,Beijing,China

国际会议

2019 2nd International Conference on Mechanical, Electronic and Engineering Technology (MEET 2019) 2019年第二届机电与工程技术国际会议

西安

英文

145-150

2019-01-19(万方平台首次上网日期,不代表论文的发表时间)