Applied Clinical Informatics, Inhaltsverzeichnis Appl Clin Inform 2013; 04(01): 88-99DOI: 10.4338/ACI-2012-11-RA-0049 Research Article Schattauer GmbH The contribution of the Vaccine adverse event Text Mining system to the classification of possible Guillain-Barré Syndrome reports T. Botsis 1 Food and Drug Administration, Center for Biologics Evaluation and Research, Rockville, Maryland, United States 2 Department of Computer Science, University of Tromsø, Norway , E. J. Woo 1 Food and Drug Administration, Center for Biologics Evaluation and Research, Rockville, Maryland, United States , R. Ball 1 Food and Drug Administration, Center for Biologics Evaluation and Research, Rockville, Maryland, United States › Institutsangaben Artikel empfehlen Abstract Volltext als PDF herunterladen Keywords KeywordsBiosurveillance and case reporting - data repositories - data mining - natural language processing - data access - integration - analysis Referenzen References 1 Varricchio F, Iskander J, Destefano F, Ball R, Pless R, Braun MM, Chen RT. Understanding vaccine safety information from the vaccine adverse event reporting system. The Pediatric Infectious Disease Journal 2004; 23 (04) 287-294. 2 Brown EG, Wood L, Wood S. The medical dictionary for regulatory activities (MedDRA). Drug Safety 1999; 20 (02) 109-117. 3 Brown EG. Using MedDRA: implications for risk management. Drug Safety 2004; 27 (08) 591-602. 4 Food and Drug Administration.. Guidance for Industry. US Department of Health and Human Services. Available from http://www.fda.gov/downloads/RegulatoryInformation/Guidances/UCM126834.pdf Last accessed: 30 October 2012 5 Bousquet C, Henegar C, Louet ALL, Degoulet P, Jaulent MC. Implementation of automated signal generation in pharmacovigilance using a knowledge-based approach. International Journal of Medical Informatics 2005; 74 7-8 563-571. 6 Bonhoeffer J, Kohl K, Chen R, Duclos P, Heijbel H, Heininger U, Jefferson T, Loupi E. The Brighton Collaboration: addressing the need for standardized case definitions of adverse events following immunization (AEFI). Vaccine 2002; 21 3-4 298-302. 7 Botsis T, Woo EJ, Ball R. Application of Information Retrieval Approaches to Case Classification in the Vaccine Adverse Event Reporting System. Drug Safety (in press). 8 Botsis T, Buttolph T, Nguyen MD, Winiecki S, Woo EJ, Ball R. Vaccine adverse event text mining system for extracting features from vaccine safety reports. Journal of the American Medical Informatics Association 2012; 19 (06) 1011-1018. 9 Botsis T, Nguyen MD, Woo EJ, Markatou M, Ball R. Text mining for the Vaccine Adverse Event Reporting System: medical text classification using informative feature selection. Journal of the American Medical Informatics Association 2011; 18 (05) 631-638. 10 Brighton Collaboration.. ABC tool: Electronic Concultant. Available from: https://brightoncollaboration org/public/what-we-do/capacity/abc html. Last accessed: 7 July 2012 11 Sejvar JJ, Kohl KS, Gidudu J, Amato A, Bakshi N, Baxter R, Burwen DR, Cornblath DR, Cleerbout J, Edwards KM. Guillain-Barré syndrome and Fisher syndrome: case definitions and guidelines for collection, analysis, and presentation of immunization safety data. Vaccine 2011; 29 (03) 599-612. 12 UMLS® Reference Manual [Internet].. Bethesda (MD): National Library of Medicine (US); 2009 Sep. Available from: http://www.ncbi.nlm.nih.gov/books/NBK9676. 13 Manning CD, Raghavan P, Schutze H. Introduction to information retrieval. 1st edition. Cambridge University Press; Cambridge: 2008 14 Harpaz R, DuMouchel W, Shah NH, Madigan D, Ryan P, Friedman C. Novel Data-Mining Methodologies for Adverse Drug Event Discovery and Analysis. Clinical Pharmacology & Therapeutics 2012; 91 (06) 1010-1021. 15 Ali AK, Hartzema AG. Assessing the association between omalizumab and arteriothrombotic events through spontaneous adverse event reporting. Journal of Asthma and Allergy 2012; 5: 1-9. 16 Harpaz R, Haerian K, Chase HS, Friedman C. Statistical Mining of Potential Drug Interaction Adverse Effects in FDA’s Spontaneous Reporting System. AMIA Annual Symposum Proceedings 2010: 281-285. 17 Kadoyama K, Sakaeda T, Tamon A, Okuno Y. Adverse event profile of tigecycline: data mining of the public version of the u.s. Food and drug administration adverse event reporting system. Biological & Pharmaceutical Bulletin 2012; 35 (06) 967-970. 18 Trifiro G, Patadia V, Schuemie MJ, Coloma PM, Gini R, Herings R, Hippisley-Cox J, Mazzaglia G, Giaquinto C, Scotti L. et al. EU-ADR healthcare database network vs. spontaneous reporting system database: preliminary comparison of signal detection. Studies in Health Technology and Informatics 2011; 166: 25-30. 19 Pearson RK, Hauben M, Goldsmith DI, Gould AL, Madigan D, O’Hara DJ, Reisinger SJ, Hochberg AM. Influence of the MedDRA hierarchy on pharmacovigilance data mining results. International Journal of Medical Informatics 2009; 78 (12) e97-e103. 20 Tolentino H, Matters M, Walop W, Law B, Tong W, Liu F, Fontelo P, Kohl K, Payne D. Concept negation in free text components of vaccine safety reports. AMIA Annual Symposium Proceedings; 2006: 1122. 21 Tolentino HD, Matters MD, Walop W, Law B, Tong W, Liu F, Fontelo P, Kohl K, Payne DC. A UMLS-based spell checker for natural language processing in vaccine safety. BMC Medical Informatics & Decision Making 2007; 7: 3.
