Literature DB >> 19745239

Application of the Apriori algorithm for adverse drug reaction detection.

M H Kuo1, A W Kushniruk, E M Borycki, D Greig.   

Abstract

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.

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Year:  2009        PMID: 19745239

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  4 in total

1.  Automatic adverse drug events detection using letters to the editor.

Authors:  Chao Yang; Padmini Srinivasan; Philip M Polgreen
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

2.  Exploration of the association rules mining technique for the signal detection of adverse drug events in spontaneous reporting systems.

Authors:  Chao Wang; Xiao-Jing Guo; Jin-Fang Xu; Cheng Wu; Ya-Lin Sun; Xiao-Fei Ye; Wei Qian; Xiu-Qiang Ma; Wen-Min Du; Jia He
Journal:  PLoS One       Date:  2012-07-16       Impact factor: 3.240

3.  Discovering Associations of Adverse Events with Pharmacotherapy in Patients with Non-Small Cell Lung Cancer Using Modified Apriori Algorithm.

Authors:  Wei Chen; Jun Yang; Hui-Ling Wang; Ya-Fei Shi; Hao Tang; Guo-Hui Li
Journal:  Biomed Res Int       Date:  2018-04-23       Impact factor: 3.411

4.  Oral administration of East Asian herbal medicine for peripheral neuropathy: A protocol for systematic review and meta-analysis with using association rule analysis to identify core herb pattern.

Authors:  Hoseok Lee; Hee-Geun Jo; Donghun Lee
Journal:  Medicine (Baltimore)       Date:  2021-11-12       Impact factor: 1.817

  4 in total

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