Annotating and recognising named entities in clinical notes

ACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf.

Volumn , Issue , 2009, Pages 18-26

  Wang, Yefeng ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL RESEARCH; COMPUTATIONAL LINGUISTICS; INFORMATION RETRIEVAL; LEARNING ALGORITHMS; MACHINE LEARNING; RANDOM PROCESSES; NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS; SUPERVISED LEARNING;

CLINICAL NOTES; CONDITIONAL RANDOM FIELD; ENTITY-TYPES; FEATURE SETS; INTENSIVE CARE; NAMED ENTITIES; RULE BASED; SUPERVISED LEARNING APPROACHES; DATA SET; FEATURES SETS; MACHINE LEARNING SYSTEMS; RULES BASED SYSTEMS;

NATURAL LANGUAGE PROCESSING SYSTEMS; RANDOM PROCESSES;

EID: 80053235919     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1667884.1667888     Document Type: Conference Paper

References (26)

1. R. Aronson. 2001. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. In Proceeding of the AMIA Symposium,17-21.
2. F. Brennan and A. Aronson 2003. Towards linking patients and clinical information: detecting UMLS concepts in e-mail. Journal of Biomedical Informatics,36(4/5),334-341.
3. A. Côté and American Veterinary Medical Association and College of American Pathologists. 2009. Snomed International. College of American Pathologists.
4. C. Friedman 2000. A broad coverage natural language processing system. In Proceedings of the AMIA Symposium,270-274.
5. C. Friedman, L. Shagina, Y. Lussier, and G. Hripcsak. 2004. Automated Encoding of Clinical Documents Based on Natural Language Processing. Journal of the American Medical Informatics Association,11(5),392-402.
6. B. Hazlehurst, R. Frost, F. Sittig, and J. Stevens. 2005. MediClass: A System for Detecting and Classifying Encounter-based Clinical Events in Any Electronic Medical Record. Journal of the American Medical Informatics Association,12(5),517-529.
7. R. Hersh, and D. Hickam. 1995. Information retrieval in medicine: The SAPHIRE experience. Journal of the American Society for Information Science,46(10),743-747.
8. Y. Huang, J. Lowe, D. Klein, and J. Cucina. 2005. Improved Identification of Noun Phrases in Clinical Radiology Reports Using a High-Performance Statistical Natural Language Parser Augmented with the UMLS Specialist Lexicon. Journal of the American Medical Informatics Association,12(3),275-285.
9. A. Jimeno, et al. 2008. Assessment of disease named entity recognition on a corpus of annotated sentences. BMC Bioinformatics,9(3).
10. D. Kim, T. Ohta, Y. Tateisi, and J. Tsujii. 2003. GENIA corpus - a semantically annotated corpus for bio-textmining. Journal of Bioinformatics, 19(1),180-182.
11. J. Lafferty et al. 2001. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data Machine learning-international workshop then conference, 282-289.
12. A. Lindberg et al. 1993. The Unified Medical Language System. Methods Inf Med.
13. M. Mandel 2006. Integrated Annotation of Biomedical Text: Creating the PennBioIE corpus. Text Mining Ontologies and Natural Language Processing in Biomedicine, Manchester, UK.
14. A. McCallum, et al. 2000. Maximum entropy Markov models for information extraction and segmentation Proc. 17th International Conf. on Machine Learning, 591-598.
15. C. N'edellec. 2005. Learning Language in Logic - Genic Interaction Extraction Challenge. Proceedings of the ICML05 Workshop on Learning Language in Logic, Bonn, 31-37.
16. V. Ogren, G. Savova, D. Buntrock, and G. Chute. 2006. Building and Evaluating Annotated Corpora for Medical NLP Systems. AMIA Annu Symp Proceeding.
17. J. Patrick, Y. Wang, and P. Budd. 2006. Automatic Mapping Clinical Notes to Medical Terminologies In Proceedings of Australasian Language Technology Workshop.
18. P. Pestian, C. Brew, P. Matykiewicz, J. Hovermale, N. Johnson, K. Cohen, and W. Duch. 2007. A Shared Task Involving Multi-label Classification of Clinical Free Text In Proceedings of BioNLP workshop.
19. R. Rabiner 1989. A tutorial on hidden Markov models and selected applications inspeech recognition Proceedings of the IEEE,77(2), 257-286.
20. A. Roberts, R. Gaizauskas, M. Hepple, G. Demetriou, Y. Guo, A. Setzer, I. and Roberts. 2007. The CLEF Corpus: Semantic Annotation of Clinical Text. AMIA Annu Symp Proceeding., Oct 11:625-629.
21. R. Tsai, L. Sung, J. Dai, C. Hung, Y. Sung, and L. Hsu. 2006. NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity BMC Bioinformatics.
22. G. Ward 1996. Moby thesaurus. http://etext.icewire.com/moby/.
23. K. Yoshida, and J. Tsujii. 2007. Reranking for Biomedical Named-Entity Recognition Proceedings of BioNLP 2007: Biological, translational, and clinical language processing, 209-216.
24. G. Zhou, J. Zhang, J. Su, D. Shen, and L. Tan. 2004. Recognizing Names in Biomedical Texts: a Machine Learning Approach BioInformatics, 20(7) 1178-1190.
25. X. Zhou, et al. 2006. MaxMatcher: Biological Concept Extraction Using Approximate Dictionary Lookup. Proc PRICAI,1145-1149.
26. Q. Zou. 2003. IndexFinder: A Method of Extracting Key Concepts from Clinical Texts for Indexing. Proc AMIA Symp,763-767.