Abstract
SNOMED is a large description logic based terminology for recording in electronic health records. Often, neither the labels nor the description logic definitions are easy for users to understand. Furthermore, information is increasingly being recorded not just using individual SNOMED concepts but also using complex expressions in the description logic (“post-coordinated” concepts). Such post-coordinated expressions are likely to be even more complex than other definitions, and therefore can have no pre-assigned labels. Automatic verbalisation will be useful both for understanding and quality assurance of SNOMED definitions, and for helping users to understand post-coordinated expressions. OntoVerbal is a system that presents a compositional terminology expressed in OWL as natural language. We describe the application of OntoVerbal to SNOMED-CT, whereby SNOMED classes are presented as textual paragraphs through the use of natural language generation technology.
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References
SNOMED-CT User Guide, http://www.ihtsdo.org/fileadmin/user_upload/Docs_01/SNOMED_CT/About_SNOMED_CT/Use_of_SNOMED_CT/SNOMED_CT_User_Guide_20090731.pdf
Baader, F., Horrocks, I., Sattler, U.: Description logics as ontology languages for the semantic web. In: Hutter, D., Stephan, W. (eds.) Mechanizing Mathematical Reasoning. LNCS (LNAI), vol. 2605, pp. 228–248. Springer, Heidelberg (2005)
Baud, R.H., Rodrigues, J.-M., Wagner, J.C., et al.: Validation of concept representation using natural language generation. Journal of the American Medical Informatics Association 841 (1997)
Callaway, C.B.: Integrating discourse markers into a pipelined natural language generation architecture. In: 41st Annual Meeting on Association for Computational Linguistics, vol. 1, pp. 264–271 (2003)
Clark, H.H.: Psycholinguistics. MIT Press, Cambridge (1999)
Dalianis, H.: Aggregation as a subtask of text and sentence planning. In: Stewman, J.H. (ed.) Florida AI Research Symposium, FLAIRS 1996, pp. 1–5 (1996)
Mann, W.C., Thompson, S.A.: Rhetorical Structure Theory: toward a functional theory of text organisation. Text 8, 243–281 (1988)
Power, R., Scott, D., Bouanyad-Agha, N.: Document structure. Computational Linguistics 29, 211–260 (2003)
Reape, M., Mellish, C.: Just what is aggregation, anyway? In: European Workshop on Natural Language Generation (1999)
Scott, D., Souza, C.S.: d.: Getting the message across in RST-based text generation. In: Mellish, C., Dale, R., Zock, M. (eds.) Current Research in Natural Language Generation, pp. 31–56. Academic Press, London (1990)
Walker, M.A., Joshi, A.K., Prince, E.F.: Centering Theory in Discourse. Oxford University Press, Oxford (1998)
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Liang, S.F., Stevens, R., Scott, D., Rector, A. (2011). Automatic Verbalisation of SNOMED Classes Using OntoVerbal. In: Peleg, M., Lavrač, N., Combi, C. (eds) Artificial Intelligence in Medicine. AIME 2011. Lecture Notes in Computer Science(), vol 6747. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22218-4_43
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DOI: https://doi.org/10.1007/978-3-642-22218-4_43
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