NDLI: Comparing data-mining algorithms developed for longitudinal observational databases

Content Provider	IEEE Xplore Digital Library
Author	Reps, J. Garibaldi, J.M. Aickelin, U. Soria, D. Gibson, J.E. Hubbard, R.B.
Copyright Year	2012
Description	Author affiliation: Clinical Sciences Building, Nottingham City Hospital, NG5 1PB, UK (Gibson, J.E.; Hubbard, R.B.) \|\| School of Computer Science, University of Nottingham, NG8 1BB, UK (Reps, J.; Garibaldi, J.M.; Aickelin, U.; Soria, D.)
Abstract	Longitudinal observational databases have become a recent interest in the post marketing drug surveillance community due to their ability of presenting a new perspective for detecting negative side effects. Algorithms mining longitudinal observation databases are not restricted by many of the limitations associated with the more conventional methods that have been developed for spontaneous reporting system databases. In this paper we investigate the robustness of four recently developed algorithms that mine longitudinal observational databases by applying them to The Health Improvement Network (THIN) for six drugs with well document known negative side effects. Our results show that none of the existing algorithms was able to consistently identify known adverse drug reactions above events related to the cause of the drug and no algorithm was superior.
Starting Page	1
Ending Page	8
File Size	261126
Page Count	8
File Format	PDF
ISBN	9781467343916
e-ISBN	9781467343923
DOI	10.1109/UKCI.2012.6335771
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-05
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Drugs Integrated circuits Databases Sociology History Statistics Medical diagnostic imaging
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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