Detecting adverse drug events with multiple representations of clinical measurements

Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014

Volumn , Issue , 2014, Pages 536-543

  Zhao, Jing ^a   Henriksson, Aron ^a   Asker, Lars ^a   Boström, Henrik ^a  

^a STOCKHOLM UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84922793428     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBM.2014.6999216     Document Type: Conference Paper

References (27)

1. J. R. Nebeker, P. Barach, and M. H. Samore, "Clarifying adverse drug events: a clinician's guide to terminology, documentation, and reporting," Annals of Internal Medicine, vol. 140, no. 10, pp. 795-801, 2004.
2. L. T. Kohn, J. M. Corrigan, M. S. Donaldson et al., To Err Is Human:: Building a Safer Health System. National Academies Press, 2000, vol. 627.
3. R. Howard, A. Avery, S. Slavenburg, S. Royal, G. Pipe, P. Lucassen, and M. Pirmohamed, "Which drugs cause preventable admissions to hospital a systematic review," British Journal of Clinical Pharmacology, vol. 63, no. 2, pp. 136-147, 2007.
4. K. Wester, A. K. Jönsson, O. Spigset, H. Druid, and S. Hägg, "Incidence of fatal adverse drug reactions: a population based study," British Journal of Clinical Pharmacology, vol. 65, no. 4, pp. 573-579, 2008.
5. B. Sibbald, "Rofecoxib (vioxx) voluntarily withdrawn from market," Canadian Medical Association Journal, vol. 171, no. 9, pp. 1027-1028, 2004.
6. C. D. Furberg and B. Pitt, "Withdrawal of cerivastatin from the world market," Curr Control Trials Cardiovasc Med, vol. 2, no. 5, pp. 205-207, 2001.
7. S. A. Goldman, "Limitations and strengths of spontaneous reports data," Clinical Therapeutics, vol. 20, pp. C40-C44, 1998.
8. P. M. Coloma, G. Trifirò, V. Patadia, and M. Sturkenboom, "Postmarketing safety surveillance," Drug Safety, vol. 36, no. 3, pp. 183-197, 2013.
9. G. N. Norén and I. R. Edwards, "Opportunities and challenges of adverse drug reaction surveillance in electronic patient records," Pharmacovigilance Review, vol. 4, no. 1, pp. 17-20, 2010.
10. L. Hazell and S. A. Shakir, "Under-reporting of adverse drug reactions," Drug Safety, vol. 29, no. 5, pp. 385-396, 2006.
11. A. Henriksson, M. Kvist, M. Hassel, and H. Dalianis, "Exploration of adverse drug reactions in semantic vector space models of clinical text," in the 29th International Conference on Machine Learning, 2012.
12. P. LePendu, S. V. Iyer, A. Bauer-Mehren, R. Harpaz, J. M. Mortensen, T. Podchiyska, T. A. Ferris, and N. H. Shah, "Pharmacovigilance using clinical notes," Clinical Pharmacology & Therapeutics, vol. 93, no. 6, pp. 547-555, 2013.
13. R. Harpaz, K. Haerian, H. S. Chase, and C. Friedman, "Mining electronic health records for adverse drug effects using regression based methods," in the 1st ACM International Health Informatics Symposium. ACM, 2010, pp. 100-107.
14. H. Jin, J. Chen, H. He, C. Kelman, D. McAullay, and C. M. O'Keefe, "Signaling potential adverse drug reactions from administrative health databases," IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 6, pp. 839-853, 2010.
15. E. Chazard, G. Ficheur, S. Bernonville, M. Luyckx, and R. Beuscart, "Data mining to generate adverse drug events detection rules," IEEE Transactions on Information Technology in Biomedicine, vol. 15, no. 6, pp. 823-830, 2011.
16. M. Y. Park, D. Yoon, K. Lee, S. Y. Kang, I. Park, S.-H. Lee, W. Kim, H. J. Kam, Y.-H. Lee, J. H. Kim et al., "A novel algorithm for detection of adverse drug reaction signals using a hospital electronic medical record database," Pharmacoepidemiology and Drug Safety, vol. 20, no. 6, pp. 598-607, 2011.
17. D. Page, V. S. Costa, S. Natarajan, A. Barnard, P. L. Peissig, and M. Caldwell, "Identifying adverse drug events by relational learning," in the 26th AAAI Conference on Artificial Intelligence, 2012, pp. 1599-1605.
18. I. Karlsson, J. Zhao, L. Asker, and H. Bostr öm, "Predicting adverse drug events by analyzing electronic patient records," in Artificial Intelligence in Medicine Lecture Notes in Computer Science. Springer, 2013, pp. 125-129.
19. J. Zhao, A. Henriksson, and H. Bostr öm, "Detecting adverse drug events using concept hierarchy of clinical codes," in IEEE International Conference on Healthcare Informatics. IEEE, 2014, pp. 285-293.
20. L. Breiman, "Random forests," Machine Learning, vol. 45, no. 1, pp. 5-32, 2001.
21. R. Caruana and A. Niculescu-Mizil, "An empirical comparison of supervised learning algorithms," in the 23rd international conference on Machine learning. ACM, 2006, pp. 161-168.
22. H. Dalianis, M. Hassel, A. Henriksson, and M. Skeppstedt, "Stockholm EPR Corpus: A Clinical Database Used to Improve Health Care," in Swedish Language Technology Conference, 2012, pp. 17-18.
23. J. Stausberg and J. Hasford, "Drug-related admissions and hospitalacquired adverse drug events in germany: a longitudinal analysis from 2003 to 2007 of icd-10-coded routine data," BMC Health Services Research, vol. 11, no. 1, p. 134, 2011.
24. H. He and E. A. Garcia, "Learning from imbalanced data," IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 9, pp. 1263-1284, 2009.
25. C. Strobl, A.-L. Boulesteix, A. Zeileis, and T. Hothorn, "Bias in random forest variable importance measures: Illustrations, sources and a solution," BMC Bioinformatics, vol. 8, no. 1, p. 25, 2007.
26. S. Garcia and F. Herrera, "An extension on" statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons. " Journal of Machine Learning Research, vol. 9, no. 12, 2008.
27. J. Demsar, "Statistical comparisons of classifiers over multiple data sets," The Journal of Machine Learning Research, vol. 7, pp. 1-30, 2006.