Skip to main content

Learning Formal Definitions for Snomed CT from Text

  • Conference paper
Artificial Intelligence in Medicine (AIME 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7885))

Included in the following conference series:

Abstract

Snomed CT is a widely used medical ontology which is formally expressed in a fragment of the Description Logic \(\mathcal{EL}\text{++}\). The underlying logics allow for expressive querying, yet make it costly to maintain and extend the ontology. In this paper we present an approach for the extraction of Snomed CT definitions from natural language text. We test and evaluate the approach using two types of texts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baader, F., Brandt, S., Lutz, C.: Pushing the \(\mathcal{EL}\) envelope. In: Proceedings of IJCAI 2005. Morgan Kaufmann (2005)

    Google Scholar 

  2. Chitsaz, M., Wang, K., Blumenstein, M., Qi, G.: Concept Learning for \(\mathcal{EL}\)  + +  by Refinement and Reinforcement. In: Anthony, P., Ishizuka, M., Lukose, D. (eds.) PRICAI 2012. LNCS, vol. 7458, pp. 15–26. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  3. Cimiano, P.: Ontology learning and population from text - algorithms, evaluation and applications. Springer (2006)

    Google Scholar 

  4. Mintz, M., Bills, S., Snow, R., Jurafsky, D.: Distant supervision for relation extraction without labeled data. In: Proceedings of ACL/AFNLP 2009, pp. 1003–1011 (2009)

    Google Scholar 

  5. Paslaru Bontas Simperl, E., Tempich, C., Sure, Y.: ONTOCOM: A cost estimation model for ontology engineering. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 625–639. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  6. Snomed Clinical Terms. College of American Pathologists, Northfield (2006)

    Google Scholar 

  7. Völker, J.: Learning expressive ontologies. PhD thesis, Universität Karlsruhe (2009)

    Google Scholar 

  8. Wächter, T., Fabian, G., Schroeder, M.: Dog4dag: Semi-automated ontology generation in OBO-Edit and Protégé. In: Proceedings of SWAT4LS 2011, pp. 119–120 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ma, Y., Distel, F. (2013). Learning Formal Definitions for Snomed CT from Text. In: Peek, N., Marín Morales, R., Peleg, M. (eds) Artificial Intelligence in Medicine. AIME 2013. Lecture Notes in Computer Science(), vol 7885. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38326-7_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38326-7_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38325-0

  • Online ISBN: 978-3-642-38326-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics