Signaling drug adverse effects in spontaneous reporting systems: A high utility itemset mining approach

B. Anup Bhat, S. V. Harish, M. Geetha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spontaneous Reporting Systems (SRS) are one of the primary sources of the Pharmacovigilance (PV) data that collect and store the reports of drug-adverse effects. In order to signal potential Adverse Drug Reactions (ADRs) from the vast set of reports from the SRS database, Frequent Itemset Mining (FIM) using the Apriori algorithm has been employed successfully. However, FIM fails to accommodate the seriousness of the reported adverse effects and merely counts the support based on the presence or absence of the drug or adverse effect in the database. In this work, Fast High Utility Itemset Mining (FHM) has been employed to accommodate the seriousness factor as a utility measure to arrive at multi-item drug-adverse effects associations. Further, the results indicate the effectiveness of the associations found in terms of Relative Reporting Ratio (RRR) to be significantly better than those of the FIM based Apriori algorithm. A few ADRs enumerated by employing FHM have been summarized which can be taken up for further clinical investigation.

Original languageEnglish
Title of host publicationMPCIT 2020 - Proceedings
Subtitle of host publicationIEEE 3rd International Conference on "Multimedia Processing, Communication and Information Technology"
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages107-111
Number of pages5
ISBN (Electronic)9780738143354
DOIs
Publication statusPublished - 11-12-2020
Event3rd IEEE International Conference on Multimedia Processing, Communication and Information Technology, MPCIT 2020 - Virtual, Shivamogga, India
Duration: 11-12-202012-12-2020

Publication series

NameMPCIT 2020 - Proceedings: IEEE 3rd International Conference on "Multimedia Processing, Communication and Information Technology"

Conference

Conference3rd IEEE International Conference on Multimedia Processing, Communication and Information Technology, MPCIT 2020
Country/TerritoryIndia
CityVirtual, Shivamogga
Period11-12-2012-12-20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Media Technology

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