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Proceedings of the AMIA Symposium logoLink to Proceedings of the AMIA Symposium
. 2000:51–55.

Limited parsing of notational text visit notes: ad-hoc vs. NLP approaches.

R C Barrows Jr 1, M Busuioc 1, C Friedman 1
PMCID: PMC2243829  PMID: 11079843

Abstract

This paper describes the extraction of structured data relevant to glaucoma diagnosis and progression from visit notes typed as "notational text" by ophthalmologists during patient encounters. We compared two text processing systems: a limited pattern matching system called GDP (Glaucoma Dedicated Parser) and MedLEE, a proven natural language processing system which is in routine use encoding findings from chest radiograph and mammogram reports at the New York-Presbyterian hospital's Columbia-Presbyterian Center. We also evaluated the use of GDP as a preprocessor program to transform notational text into constructions recognizable by MedLEE. These systems have been evaluated according to their recall and precision in the particular task of processing a corpus of "notational text" documents to extract information related to glaucoma disease.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Baud R. H., Lovis C., Rassinoux A. M., Scherrer J. R. Morpho-semantic parsing of medical expressions. Proc AMIA Symp. 1998:760–764. [PMC free article] [PubMed] [Google Scholar]
  2. Baud R. H., Rassinoux A. M., Scherrer J. R. Natural language processing and semantical representation of medical texts. Methods Inf Med. 1992 Jun;31(2):117–125. [PubMed] [Google Scholar]
  3. Friedman C. Towards a comprehensive medical language processing system: methods and issues. Proc AMIA Annu Fall Symp. 1997:595–599. [PMC free article] [PubMed] [Google Scholar]
  4. Haug P. J., Koehler S., Lau L. M., Wang P., Rocha R., Huff S. M. Experience with a mixed semantic/syntactic parser. Proc Annu Symp Comput Appl Med Care. 1995:284–288. [PMC free article] [PubMed] [Google Scholar]
  5. Hripcsak G., Friedman C., Alderson P. O., DuMouchel W., Johnson S. B., Clayton P. D. Unlocking clinical data from narrative reports: a study of natural language processing. Ann Intern Med. 1995 May 1;122(9):681–688. doi: 10.7326/0003-4819-122-9-199505010-00007. [DOI] [PubMed] [Google Scholar]
  6. Hripcsak G., Knirsch C. A., Jain N. L., Pablos-Mendez A. Automated tuberculosis detection. J Am Med Inform Assoc. 1997 Sep-Oct;4(5):376–381. doi: 10.1136/jamia.1997.0040376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Sager N., Lyman M., Bucknall C., Nhan N., Tick L. J. Natural language processing and the representation of clinical data. J Am Med Inform Assoc. 1994 Mar-Apr;1(2):142–160. doi: 10.1136/jamia.1994.95236145. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Spyns P. Natural language processing in medicine: an overview. Methods Inf Med. 1996 Dec;35(4-5):285–301. [PubMed] [Google Scholar]
  9. Zweigenbaum P. MENELAS: an access system for medical records using natural language. Comput Methods Programs Biomed. 1994 Oct;45(1-2):117–120. doi: 10.1016/0169-2607(94)90029-9. [DOI] [PubMed] [Google Scholar]

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