Text mining for the Vaccine Adverse Event Reporting System: medical text classification using informative feature selection

@article{Botsis2011TextMF,
  title={Text mining for the Vaccine Adverse Event Reporting System: medical text classification using informative feature selection},
  author={T. Botsis and M. Nguyen and E. Woo and M. Markatou and R. Ball},
  journal={Journal of the American Medical Informatics Association : JAMIA},
  year={2011},
  volume={18 5},
  pages={
          631-8
        }
}
  • T. Botsis, M. Nguyen, +2 authors R. Ball
  • Published 2011
  • Computer Science, Medicine
  • Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE The US Vaccine Adverse Event Reporting System (VAERS) collects spontaneous reports of adverse events following vaccination. Medical officers review the reports and often apply standardized case definitions, such as those developed by the Brighton Collaboration. Our objective was to demonstrate a multi-level text mining approach for automated text classification of VAERS reports that could potentially reduce human workload. DESIGN We selected 6034 VAERS reports for H1N1 vaccine that… Expand
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