Skip to main content
Proceedings of the AMIA Symposium logoLink to Proceedings of the AMIA Symposium
. 1998:760–764.

Morpho-semantic parsing of medical expressions.

R H Baud 1, C Lovis 1, A M Rassinoux 1, J R Scherrer 1
PMCID: PMC2232116  PMID: 9929321

Abstract

The task of editing, indexing, storing, and retrieving medical expressions within medical records remains the main objective for the years to come. Therefore, the need for a parser with semantic capabilities able to robustly extract an essential part of the knowledge embedded in the medical record is paramount. The minimal requirements before considering clinical trials are that such a system has to be in position to handle any source of medical information and to conveniently grasp the main key concepts with low silence, good recognition of modalities and acceptable noise. This paper shows that the potential of morpho-semantic parsing is high to meet these conditions. This technique is an important complement to the traditional lexical approach and to expression-oriented systems like controlled vocabularies.

Full text

PDF
760

Selected References

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

  1. Baud R. H., Rassinoux A. M., Lovis C., Wagner J., Griesser V., Michel P. A., Scherrer J. R. Knowledge sources for Natural Language Processing. Proc AMIA Annu Fall Symp. 1996:70–74. [PMC free article] [PubMed] [Google Scholar]
  2. Baud R. H., Rassinoux A. M., Wagner J. C., Lovis C., Juge C., Alpay L. L., Michel P. A., Degoulet P., Scherrer J. R. Representing clinical narratives using conceptual graphs. Methods Inf Med. 1995 Mar;34(1-2):176–186. [PubMed] [Google Scholar]
  3. Evans D. A., Rothwell D. J., Monarch I. A., Lefferts R. G., Cote R. A. Toward representations for medical concepts. Med Decis Making. 1991 Oct-Dec;11(4 Suppl):S102–S108. [PubMed] [Google Scholar]
  4. Hersh W. R., Campbell E. H., Evans D. A., Brownlow N. D. Empirical, automated vocabulary discovery using large text corpora and advanced natural language processing tools. Proc AMIA Annu Fall Symp. 1996:159–163. [PMC free article] [PubMed] [Google Scholar]
  5. Lindberg D. A., Humphreys B. L., McCray A. T. The Unified Medical Language System. Methods Inf Med. 1993 Aug;32(4):281–291. doi: 10.1055/s-0038-1634945. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Lovis C., Michel P. A., Baud R., Scherrer J. R. Word segmentation processing: a way to exponentially extend medical dictionaries. Medinfo. 1995;8(Pt 1):28–32. [PubMed] [Google Scholar]
  7. Nazarenko A., Zweigenbaum P., Bouaud J., Habert B. Corpus-based identification and refinement of semantic classes. Proc AMIA Annu Fall Symp. 1997:585–589. [PMC free article] [PubMed] [Google Scholar]
  8. Norton L. M., Pacak M. G. Morphosemantic analysis of compound word forms denoting surgical procedures. Methods Inf Med. 1983 Jan;22(1):29–36. [PubMed] [Google Scholar]
  9. Rassinoux A. M., Wagner J. C., Lovis C., Baud R. H., Rector A., Scherrer J. R. Analysis of medical texts based on a sound medical model. Proc Annu Symp Comput Appl Med Care. 1995:27–31. [PMC free article] [PubMed] [Google Scholar]
  10. Rector A. L., Solomon W. D., Nowlan W. A., Rush T. W., Zanstra P. E., Claassen W. M. A Terminology Server for medical language and medical information systems. Methods Inf Med. 1995 Mar;34(1-2):147–157. [PubMed] [Google Scholar]

Articles from Proceedings of the AMIA Symposium are provided here courtesy of American Medical Informatics Association

RESOURCES