贝叶斯网络在护理真实世界数据的应用及Tetrad实现  

Application of bayesian network in nursing real-world data and implementation of tetrad

作　　者：李玉娟 梁会岭 王巧丽 李巧 Li Yujuan;Liang Huiling;Wang Qiaoli;Li Qiao(Department of Stomatology,Characteristic Medical Center of the Chinese People's Armed Police Force,Tianjin 300162,China)

机构地区：[1]中国人民武装警察部队特色医学中心口腔科,天津300162

出　　处：《中国实用护理杂志》2022年第34期2698-2702,共5页Chinese Journal of Practical Nursing

摘　　要：目的介绍贝叶斯网络在护理真实世界数据中的应用及Tetrad软件实现,为医学科研人员提供方法学应用参考。方法以真实世界数据糖尿病预测诊断为例,使用UCI机器学习数据库Pima-Indian Diabetes数据集为实例数据,根据Tetrad软件贝叶斯网络构建顺序进行贝叶斯网络推理。结果当筛查者年龄≥30岁、糖耐量异常、餐后2 h血清胰岛素异常、BMI异常、家族家系遗传指数较大时糖尿病发生的概率由34.99%增涨为83.33%。结论通过Tetrad软件实现的贝叶斯网络为真实世界数据因果推断提供了有力工具,促使变量间的依赖关系得到客观定量的解释。Objective It introduced the application of bayesian network in real-world data and the implementation of Tetrad software,so as to provide methodological application reference for medical researchers.Methods Real-world data for diabetes diagnosis had been taken as an example.UCI machine learning database Pima-Indian-diabetes data set was used as case data,Bayesian network ratiocination was carried out according to the construction order of bayesian network of Tetrad software.Results When the screening age was over 30 years old,impaired glucose tolerance,abnormal serum insulin two hours after meal,body weight index and family genetic index were large,the probability of diabetes onset from 34.99%to 83.33%.Conclusions The bayesian network realized by Tetrad software provides a powerful tool for causal inference of real-world data,and promoted the objective and quantitative interpretation of the dependence between variables.

关 键 词：贝叶斯网络 真实世界数据 Tetrad软件 

分 类 号：R47[医药卫生—护理学]