Application of Information Retrieval Approaches to Case Classification in the Vaccine Adverse Event Reporting System
- 24 May 2013
- journal article
- research article
- Published by Springer Science and Business Media LLC in Drug Safety
- Vol. 36 (7), 573-582
- https://doi.org/10.1007/s40264-013-0064-4
Abstract
Automating the classification of adverse event reports is an important step to improve the efficiency of vaccine safety surveillance. Previously we showed it was possible to classify reports using features extracted from the text of the reports.This publication has 16 references indexed in Scilit:
- The BioLexicon: a large-scale terminological resource for biomedical text miningBMC Bioinformatics, 2011
- Text mining for the Vaccine Adverse Event Reporting System: medical text classification using informative feature selectionJournal of the American Medical Informatics Association, 2011
- Use abstracted patient-specific features to assist an information-theoretic measurement to assess similarity between medical casesJournal of Biomedical Informatics, 2008
- Introduction to Information RetrievalPublished by Cambridge University Press (CUP) ,2008
- Measures of semantic similarity and relatedness in the biomedical domainJournal of Biomedical Informatics, 2007
- BioThesaurus: a web-based thesaurus of protein and gene namesBioinformatics, 2005
- Understanding vaccine safety information from the Vaccine Adverse Event Reporting SystemThe Pediatric Infectious Disease Journal, 2004
- The Brighton Collaboration: addressing the need for standardized case definitions of adverse events following immunization (AEFI)Vaccine, 2002
- The Medical Dictionary for Regulatory Activities (MedDRA)Drug Safety, 1999
- The Unified Medical Language System: An Informatics Research CollaborationJournal of the American Medical Informatics Association, 1998