Data mining in spontaneous reports.

Abstract:

:The increasing size of spontaneous report data sets and the increasing capability for screening such data due to increases in computational power has led to a recent increase in interest and use of data mining on such data. While data mining plays an important role in the analysis of spontaneous reports, there is general debate on how and when data mining should be best performed. While the cornerstone principles for data mining of spontaneous reports have been in place since the 1960s, several significant changes have occurred to make their use widespread. Superficially the Bayesian methods seem unnecessarily complex, particularly given the nature of the data, but in practice implementation in Bayesian framework gives clear benefits. There are difficulties evaluating the performance of the methods, but they work and save resources in managing large data sets. The use of neural networks allows more sophisticated pattern recognition to be performed.

authors

Bate A,Edwards IR

doi

10.1111/j.1742-7843.2006.pto_232.x

subject

Has Abstract

pub_date

2006-03-01 00:00:00

pages

324-30

issue

3

eissn

1742-7835

issn

1742-7843

pii

PTOpto_232

journal_volume

98

pub_type

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