Discovering Novel Adverse Drug Events Using Natural Language Processing and Mining of the Electronic Health Record
This talk presents an overview of our research in use of medical knowledge, natural language processing, the electronic health record, and statistical methods to automatically discover novel adverse drug events, which are serious problems world-wide.
KeywordsPharmacovigilance natural language processing electronic health records patient safety adverse drug events
Unable to display preview. Download preview PDF.
- 3.Schneeweiss, S., Hasford, J., Gottler, M., Hoffmann, A., Riethling, A.K., Avorn, J.: Admissions caused by adverse drug events to internal medicine and emergency departments in hospitals: a longitudinal population-based study. Eur. J. Clin. Pharmacol. 58(4), 285–291 (2002)CrossRefPubMedGoogle Scholar
- 6.Goldman, S., Kennedy, D., Graham, D., et al.: The clinical impact of adverse event reporting. Center for Drug Evaluation and Research. Food and Drug Administration (1996)Google Scholar
- 13.Wang, X., Friedman, C., Chused, A., Markatou, M., Elhadad, N.: Automated knowledge acquisition from clinical narrative reports. AMIA Annu. Symp. Proc., 783–777 (2008)Google Scholar
- 16.Wang, X., Hripcsak, G., Friedman, C.: Characterizing environmental and phenotypic associations using information theory and electronic health records. In: 2009 AMIA Summit, March 15, p. 134 (full paper selected for publication in BMC Bioinformatics) (2009)Google Scholar