血尿酸与慢性代谢性疾病的连续型和离散型贝叶斯网络效果比较
Comparison of Continuous and Discrete Bayesian Network Models for Uric Acid and Related Metabolic Indicators
崔宇 1宋伟梅 1任浩 1王旭春 1乔宇超 1赵执扬 1任家辉 1仇丽霞1
作者信息
- 1. 山西医科大学卫生统计教研室(030001)
- 折叠
摘要
目的 建立血尿酸与相关代谢性指标的连续型和离散型贝叶斯网络模型,探寻血尿酸的影响因素,并比较两种网络结果的特点和优劣.方法 利用山西省 2015 年慢性病监测的血尿酸及其代谢性疾病的特征指标共 4646 例,采用(improved partial-correlation-based,IPCB)算法建立血尿酸的连续型贝叶斯网络,同时将上述指标离散化,采用(max-min hill-climbing,MMHC)建立高尿酸的离散贝叶斯网络.结果 离散贝叶斯网络发现 14 条边,其中甘油三酯和舒张压异常与高尿酸直接关系,导致高尿酸的发生;年龄为间接因素;而连续贝叶斯网络共包含 24 条有向边,年龄、TG、LDL、HDL、SP、DP与尿酸水平直接相关,随着年龄、TG、LDL的增大和HDL的降低,尿酸水平升高,而尿酸水平升高又导致SP、DP升高;TC与尿酸间接相关.结论 两种网络模型适应的资料类型不同,但连续型贝叶斯网络发现的直接相关因素更多,整体解释度更好.
Abstract
Objective The continuous and discrete Bayesian network models of serum uric acid and related metabolic indexes were established to explore the influencing factors of serum uric acid and compare the characteristics and advantages of the results of the two networks.Methods A total of 4646 patients with serum uric acid and metabolic diseases from chronic disease monitoring in Shanxi Province in 2015 were selected.IPCB algorithm was used to establish a continuous Bayesian network of serum uric acid.Meanwhile,the above indicators were discretized,and MMHC was used to establish a discrete Bayesian network of high uric acid.Results The discrete Bayesian network found 14 edges,in which triglyceride and diastolic blood pressure abnormalities were directly related to the occurrence of high uric acid,leading to the occurrence of high uric acid.Age was an indirect factor;Age,TG,LDL,HDL,SP and DP are directly related to uric acid level.With the increase of age,TG and LDL and the decrease of HDL,uric acid level increases,while the increase of uric acid level leads to the increase of SP and DP.TC is indirectly related to uric acid.Conclusion The two network models adapt to different data types,but the continuous Bayesian network has more direct correlation factors and better overall explanatory degree.
关键词
连续型贝叶斯网络/IPCB算法/血尿酸/代谢性指标/相关因素Key words
Continuous Bayesian network/IPCB algorithm/Blood uric acid/Metabolic indicators/Relevant factor引用本文复制引用
出版年
2024
NETL
NSTL
万方数据