Influence of module order on rule-based de-identification of personal names in electronic patient records written in swedish

Proceedings of the 7th International Conference on Language Resources and Evaluation, LREC 2010

Volumn , Issue , 2010, Pages 3442-3446

  Carlsson, Elin ^a   Dalianis, Hercules ^a  

^a STOCKHOLM UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

SPEECH PROCESSING;

DE-IDENTIFICATION; ELECTRONIC PATIENT RECORD; PRECISION AND RECALL; RECALL AND PRECISION; RESEARCH QUESTIONS; RULE-BASED METHOD; SENSITIVE INFORMATIONS; TRAINING MATERIAL;

LEARNING SYSTEMS;

EID: 84906743091     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. N. Chinchor. 1997. MUC-7 Named Entity Task Definition. [Online], Published 17 september. Available at: http://acl.ldc.upenn.edu/muc7/netask.html [Accessed 5 March 2010].
2. H. Dalianis and E. Åström. 2001. SweNam - A Swedish Named Entity recognizer. Its construction, training and evaluation. Technical report, TRITA-NA-P0113, IPLab-189, NADA, KTH.
3. H. Dalianis and S. Velupillai. 2010. De-identifying Swedish Clinical Text - Refinement of a Gold Standard and Experiments with Conditional Random Fields. To be published in Journal of Biomedical Semantics.
4. H. Dalianis, M. Hassel, and S. Velupillai. 2009. The Stockholm EPR Corpus - Characteristics and Some Initial Findings. In Proceedings of the 14th International Symposium for Health Information Management Research - ISHIMR 2009. Evaluation and implementation of e-health and health information initiatives: international perspectives, pages 243-249, Kalmar, Sweden, 14-16 October, 2009.
5. M. Douglass, G.D. Clifford, A. Reisner, W.J. Long, G.B. Moody, and R.G. Mark. 2005. De-identification algorithm for free-text nursing notes. Computers in Cardiology 2005, 32:331-334.
6. HIPAA. 2003. HIPAA Privacy Rule and Public Health: Guidance from CDC and the U.S. Department of Health and Human Services. Centers for Disease Control and Prevention. MMWR, 52, April. Available at: http://www.cdc.gov/mmwr/pdf/other/m2e411.pdf (Accessed March 22, 2010).
7. O. Knutsson, J. Bigert, and V. Kann. 2003. A Robust Shallow Parser for Swedish. In Proc. 14th Nordic Conf. on Comp. Ling. NODALIDA-2003.
8. D. Kokkinakis and A. Thurin. 2007. Identification of entity references in hospital discharge letters. In Proceedings of the 16th Nordic Conference of Computational Linguistics NODALIDA-2007, pages 329-332, University of Tartu.
9. A. Mikheev, M. Moens, and C. Grover. 1999. Named entity recognition without gazetteers. In Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics, pages 1-8, Morristown, NJ, USA. Association for Computational Linguistics.
10. I. Neamatullah, M.M. Douglass, L.H. Lehman, A. Reisner, M. Villarroel, W.J. Long, P. Szolovits, G.B. Moody, R.G. Mark, and G.D. Clifford. 2008. Automated de-identification of free-text medical records. BMC Medical Informatics and Decision Making, 8:32.
11. L. Sweeney. 1996. Replacing Personally-Identifying Information in Medical Records, the Scrub System. In Proceedings of The AMIA Annual. Fall Symposium 1996, pages 333-337.
12. S.M. Thomas, B. Mamlin, G. Schadow, and C. McDonald. 2002. A Successful Technique for Removing Names in Pathology Reports Using an Augmented Search and Replace Method. In Proceedings of the AMIA Annual Symposium 2002, pages 777-781.
13. Ö. Uzuner, Y. Luo, and P. Szolovits. 2007. Evaluating the state-of-the-art in automatic de-identification. Journal of the American Medical Informatics Association, 14(5):550-563.
14. Ö. Uzuner, T.C. Sibanda, Y. Luo, and P. Szolovits. 2008. A de-identifier for medical discharge summaries. Artificial Intelligence in Medicine, 42(1):13-35.
15. S. Velupillai, H. Dalianis, M. Hassel, and G.H. Nilsson. 2009. Developing a standard for de-identifying electronic patient records written in Swedish: precision, recall and F-measure in a manual and computerized annotation trial. International Journal of Medical Informatics special issue on Mining of Clinical and Biomedical Text and Data.