基于数据挖掘的疾病并发症发现方法研究:以2型糖尿病为例
Research on Discovery Methods of Diseases Complications Based on Data Mining:Illustrated by the Example of Type 2 Diabetes
乔岩 1郑利涛 2李金林2
作者信息
- 1. 郑州大学管理学院,郑州 河南 450001
- 2. 北京理工大学管理学院,北京 100081
- 折叠
摘要
为提高临床复杂疾病并发症诊断和预测的准确性,进而辅助医疗人员及患者科学决策与治疗,以2型糖尿病为例探索了基于关联规则数据挖掘技术的疾病并发症发现方法.研究发现2型糖尿病的18条重要强关联规则,揭示了 2型糖尿病常见并发症的关联方式,其得到了医学专家的临床验证.本文的研究方法对于复杂疾病并发症的发现、疾病关联知识库的构建以及并发症预防和诊疗等都有着重要的参考意义.
Abstract
In order to diagnose and predict the complications of clinical complex diseases more accurately and assist doctors and patients to make scientific decision and treatment,this paper,taking type 2 diabetes as an example,explores the methods of discovery of disease complications based on data mining technology of association rules.The results show 18 important strong association rules,revealing the link mode of common complications of type 2 diabetes,which has been verified clinically by medical experts.The research methods of this paper have significant reference meaning for the discovery of complex disease complications,the construction of disease association knowledge base,and the prevention and treatment of complications.
关键词
数据挖掘/关联规则/并发症Key words
data mining/association rules/complications引用本文复制引用
基金项目
国家自然科学基金(72202217)
国家自然科学基金(71972012)
中国博士后科学基金面上项目(2023M743163)
郑州大学教育教学改革研究与实践重点项目(2023ZZUJGXM028)
出版年
2024
NETL
NSTL
万方数据