Kuo M H, Kushniruk A W, Borycki E M, Greig D
School of Health Information Science, University of Victoria, BC, Canada.
Stud Health Technol Inform. 2009;148:95-101.
The objective of this research is to assess the suitability of the Apriori association analysis algorithm for the detection of adverse drug reactions (ADR) in health care data. The Apriori algorithm is used to perform association analysis on the characteristics of patients, the drugs they are taking, their primary diagnosis, co-morbid conditions, and the ADRs or adverse events (AE) they experience. This analysis produces association rules that indicate what combinations of medications and patient characteristics lead to ADRs. A simple data set is used to demonstrate the feasibility and effectiveness of the algorithm.
本研究的目的是评估Apriori关联分析算法在医疗保健数据中检测药物不良反应(ADR)的适用性。Apriori算法用于对患者特征、正在服用的药物、主要诊断、合并症以及他们经历的ADR或不良事件(AE)进行关联分析。该分析产生关联规则,表明药物和患者特征的哪些组合会导致ADR。使用一个简单的数据集来证明该算法的可行性和有效性。