Automatic extraction of relations between medical concepts in clinical texts

Journal of the American Medical Informatics Association

Volumn 18, Issue 5, 2011, Pages 594-600

  Rink, Bryan ^a   Harabagiu, Sanda ^a   Roberts, Kirk ^a  

^a The University of Texas at Dallas   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONCEPT ANALYSIS; ELECTRONIC MEDICAL RECORD; MACHINE LEARNING; MEDICAL INFORMATICS; MEDICAL INFORMATION; MEDICAL LITERATURE; SUPPORT VECTOR MACHINE;

DATA MINING; DECISION SUPPORT SYSTEMS, CLINICAL; ELECTRONIC HEALTH RECORDS; HUMANS; INTERNET; NATURAL LANGUAGE PROCESSING; SUPPORT VECTOR MACHINES;

EID: 80053268344     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2011-000153     Document Type: Article

References (17)

1. Uzuner O, South BR, Shen S, et al. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text. J Am Med Inform Assoc 2011;18:552-6.
2. Aly M. Survey on Multiclass Classification Methods. Technical report, California Institute of Technology, 2005.
3. Kulick S, Bies A, Liberman M, et al. Integrated annotation for biomedical information extraction. In: Proc. of the Human Language Technology Conference and the Annual Meeting of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL), 2004.
4. Fellbaum C. WordNet: An Electronic Lexical Database. MA: MIT press Cambridge, 1998.
5. Stone PJ, Dunphy DC, Smith MS, et al. The General Inquirer: a Computer Approach to Content Analysis. MA: MIT Press Cambridge, 1966.
6. Fan RE, Chang KW, Hsieh CJ, et al. LIBLINEAR: a library for large linear classification. J Mach Learn Res 2008;9:1871-4.
7. Chang CC, Lin CJ. LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2011;2:27:1-27:27.
8. Pradhan S, Ward W, Hacioglu K, et al. Shallow semantic parsing using support vector machines. Proceedings of HLT/NAACL-2004, 2004:1-8.
9. Palmer M, Gildea D, Kingsbury P. The proposition bank: an annotated corpus of semantic roles. Comput Ling 2005:71-106.
10. Levenshtein VI. Binary codes capable of correcting deletions, insertions, and reversals. Sov Phys Dokl 1966;10:707-10.
11. de Marneffe M, Manning CD. The stanford typed dependencies representation. In: Coling 2008: Proceedings of the workshop on Cross-Framework and Cross-Domain Parser Evaluation. Manchester, United Kingdom: Association for Computational Linguistics, 2008:1-8.
12. McCallum AK. Mallet: a machine learning for language toolkit. 2002. http://mallet.cs.umass.edu.
13. Joachims T. SVMLight: support vector machine. SVM-Light Support Vector Machine. University of Dortmund, 1999:4. http://svmlight.joachims.org/.
14. Aronson AR. Effective mapping of biomedical text to the UMLS metathesaurus: the MetaMap program. Proc AMIA Symp 2001:17-21.
15. Lindberg DA, Humphreys BL, McCray AT. The unified medical language system. Methods Inf Med 1993;32:281-91.
16. Roberts K, Harabagiu SM. A flexible framework for deriving assertions from electronic medical records. J Am Med Inform Assoc 2011;18:568-73.
17. Wolpert DH. Stacked generalization. Neural networks 1992;5:241-59.