Fuzzy set analysis of Australian drug safety data

Title: Fuzzy set analysis of Australian drug safety data
Creator: Mammadov, Musa; Saunders, Gary
Date: 2002
Type: Text; Conference paper
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/43744
Identifier: vital:1453
Abstract: This report describes a preliminary analysis of the Australian Adverse Drug Reaction Database (ADRAC) using a new approach, which is being developed for the analysis of this drug safety data. This differs significantly from the statistical methods that have been used in that we utilize vectors of degrees to define drug-reaction relationships. A quasi-classification algorithm was developed to discover drugs associated with adverse reactions and possible drug-drug interactions. The machine learning algorithm FDM (Fuzzy Derivative Method) was used to predict good and bad outcomes based on observed reactions and potential vectors of degrees. This work extends existing methods for drug safety analysis and should also be of general interest in the field of data mining.; E1
Publisher: Melbourne : ACTA Press
Relation: Paper presented at HIC 2002, Melbourne : 5th August, 2002
Rights: Copyright Unknown
Rights: This metadata is freely available under a CCO license
Subject: Drug safety; Fuzzy set analysis
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