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Medical Natural Language Systems:A Review
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Medication information is one of the free text clinical data in medical records. It is difficult to access medical records due to healthcare safety and patient information security. Clinical narratives are differing due to multilingualism, clinical report formats. Clinical information can be extracted with Natural Language Processing System based on medical domain. This paper contains a short review on NLP systems used for medical domain. Medical natural language systems are different due to their use of different applications in medical domain.
Keywords
Clinical Report, Natural Language Processing.
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- C. Friedman, “Towards a comprehensive medical language processing system: Methods and issues,” Proceedings of the AMIA Annual Fall Symposium: American Medical Informatics Association, pp. 595-599, 1997.
- Koehler, and B. Spencer, “SymText: A natural language understanding system for encoding free text medical data,” Doctor Dissertation, University of Utah, 1998.
- L. M. Christensen, P. J. Haug, and M. Fiszman, “MPLUS: A probabilistic medical language understanding system,” Proceedings of the Workshop on Natural Language Processing in the Biomedical Domain: Association for Computational Linguistics, pp. 29-36, 2002.
- B. Hazlehurst, H. R. Frost, D. F. Sittig, and V. J. Stevens, “MediClass: A system for detecting and classifying encounter-based clinical events in any electronic medical record,” Journal of the American Medical Informatics Association, vol. 12, no. 5, pp. 517-529, 2005.
- S. Goryachev, M. Sordo, and Q. T. Zeng, “A suite of natural language processing tools developed for the I2B2 project,” AMIA Annual Symposium Proceedings, p. 931, 2006.
- G. K. Savova, J. J. Masanz, P. V. Ogren, J. Zheng, S. Sohn, K. C. Kipper-Schuler, and C. G. Chute, “Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): Architecture, component evaluation and applications,” Journal of the American Medical Informatics Association, vol. 17, no. 5, pp. 507-513, 2010.
- A. R. Aronson, and F.-M. Lang, “An overview of MetaMap: Historical perspective and recent advances,” Journal of the American Medical Informatics Association, vol. 17, no. 3, pp. 229-236, 2010.
- H. Xu, S. P. Stenner, S. Doan, K. B. Johnson, L. R. Waitman, and J. C. Denny, “MedEx: A medication information extraction system for clinical narratives,” Journal of the American Medical Informatics Association, vol. 17, no. 1, pp. 19-24, 2010.
- V. Garla, V. L. Re, Z. Dorey-Stein, F. Kidwai, M. Scotch, J. Womack, A. Justice, and C. Brandt, “The Yale cTAKES extensions for document classification: Architecture and application,” Journal of the American Medical Informatics Association, vol. 18, no. 5, pp. 614-620, 2011.
- Y. K. Lin, H. Chen, and R. A. Brown, “MedTime: A temporal information extraction system for clinical narratives,” Journal of Biomedical Informatics, pp. 20-28, 2013.
- S. Sohn, C. Clark, S. R. Halgrim, S. P. Murphy, C. G. Chute, and H. Liu, “MedXN: An open source medication extraction and normalization tool for clinical text,” Journal of the American Medical Informatics Association, vol. 21, no. 5, pp. 858-865, 2014.
- F. R. Goss, J. M. Plasek, J. J. Lau, D. L. Seger, F. Y. Chang, and L. Zhou, “An evaluation of a natural language processing tool for identifying and encoding allergy information in emergency department clinical notes,” AMIA Annual Symposium Proceedings, pp. 580-588, 2014.
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