Current application status of association rule mining in real-world study on drug safety
10.12173/j.issn.1005-0698.202410006
- VernacularTitle:关联规则挖掘在药品安全性真实世界研究中的应用现状
- Author:
Xiaoli XU
1
;
Xinyang WANG
;
Jingfei YANG
;
Mengjiao HE
;
Pengcheng LIU
Author Information
1. 中国药科大学国际医药商学院(南京 211198)
- Publication Type:Journal Article
- Keywords:
Association rule mining;
Drug safety;
Apriori algorithm;
Real world study;
Pharmacovigilance
- From:
Chinese Journal of Pharmacoepidemiology
2025;34(5):578-588
- CountryChina
- Language:Chinese
-
Abstract:
An overview of the application of association rule mining(ARM)in real-world study(RWD)on drug safety to inform pharmacovigilance real-world data analysis.The applications of ARM in RWD of drug safety were divided into single drug/vaccine signal detection,combined medication risk mining,multidimensional risk factor analysis and adverse drug event occurrence characterization based on passive monitoring data;medication characterization pattern analysis,auxiliary epidemiological study design and risk mining of the whole dataset based on active monitoring data.In general,foreign scholars pay more attention to method rule setting,performance evaluation and application research,while domestic scholars pay more attention to multidimensional risk factor analysis,adverse drug event occurrence pattern,and clinical drug use characteristics research.With the accumulation of medical data and the continuous development of data mining technology,ARM may provide new ideas for RWD on drug safety.
