Nate Blaylock
ABSTRACT
In this paper, we present our ongoing work towards an OWL-based framework for extracting a variety of information (including patient history) from clinical texts. Our framework integrates a well-known natural language processing (NLP) system by converting its ontology and output logical form interpretation into the Web Ontology Language (OWL). The OWL-based Semantic Query-Enhanced Web Rule Language (SQWRL) is then used as a platform for authoring Semantic Web-aware rules for extracting information of interest from the OWL knowledge based created from parsing a clinical report. We also describe our ongoing work on using this system for extracting a timeline-based patient medical record from the history of present illness section of clinical texts.
- J. Allen, D. Byron, M. Dzikovska, G. Ferguson, L. Galescu, and A. Stent. An architecture for a generic dialogue shell. Journal of Natural Language Engineering special issue on Best Practices in Spoken Language Dialogue Systems Engineering, 6(3):1--16, December 2000. Google Scholar
Digital Library
- J. F. Allen, M. Swift, and W. de Beaumont. Deep semantic analysis of text. In Symposium on Semantics in Systems for Text Processing (STEP 2008) Shared Task: Comparing Semantic Representations, Venice, Italy, September 22--24 2008. Google ScholarDigital Library
- A. R. Aronson and F.-M. Lang. An overview of MetaMap: historical perspective and recent advances. Journal of the American Medical Informatics Association, 17:(3):229--236, May 2010.Google Scholar
- N. Blaylock, B. Swain, and J. Allen. Mining geospatial path data from natural language descriptions. In Proceedings of the 1st ACM SIGSPATIAL GIS International Workshop on Querying and Mining Uncertain Spatio-Temporal Data, Seattle, Washington, November 3 2009.Google Scholar
- M. O. Dzikovska, J. F. Allen, and M. D. Swift. Linking semantic and knowledge representations in a multi-domain dialogue system. Journal of Logic and Computation, 18(3):405--430, 2008. Google ScholarDigital Library
- L. Galescu, N. Blaylock, J. Allen, W. de Beaumont, H. Jung, and M. Swift. A deep NLP system for extracting knowledge from clinical text: Application to the 2010 i2b2/VA concept extraction task. In Fourth i2b2/VA Shared-Task and Workshop Challenges in Natural Language Processing for Clinical Data, Washington, DC, November 12--13 2010.Google Scholar
- H. Jung, N. Blaylock, J. Allen, W. de Beaumont, L. Galescu, and M. Swift. Building timelines from narrative clinical records: Initial results based-on deep natural language understanding. In ACL Workshop on Biomedical Natural Language Processing (BioNLP), Portland, Oregon, 2011. Under review. Google ScholarDigital Library
- M. H. Manshadi, J. F. Allen, and M. Swift. Toward a universal underspecified semantic representation. In 13th Conference on Formal Grammar (FG 2008), Hamburg, Germany, August 9--10 2008.Google Scholar
- S. M. Meystre, G. K. Savova, K. C. Kipper-Schuler, and J. F. Hurdle. Extracting information from textual documents in the electronic health record: a review of recent research. Yearbook of Medical Informatics, pages 128--144, 2008.Google Scholar
- M. O'Connor and A. Das. SQWRL: a query language for OWL. In OWL: Experiences and Directions (OWLED), Fifth International Workshop, Chantilly, Virginia, 2009.Google Scholar
- G. K. Savova, J. J. Masanz, P. V. Ogren, J. Zheng, S. Sohn, K. C. Kippe-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, 17(5):507--513, September 2010.Google ScholarCross Ref
- M. Swift, N. Blaylock, J. Allen, W. de Beaumont, L. Galescu, and H. Jung. Augmenting a deep natural language processing system with UMLS. In Proceedings of the Fourth Symposium on Semantic Mining in Biomedicine (SMBM 2010), Hinxton, UK, October 2010.Google Scholar
- N. UzZaman and J. F. Allen. Event and temporal expression extraction from raw text: First step towards a temporally aware system. International Journal of Semantic Computing, To appear, 2011.Google Scholar
- D. C. Wimalasuriya and D. Dou. Ontology-based information extraction: An introduction and a survey of current approaches. Journal of Information Science, 36(3):306--323, 2010. Google ScholarDigital Library
Index Terms
- Towards an OWL-based framework for extracting information from clinical texts
Recommendations
OWL rules: A proposal and prototype implementation
Although the OWL Web Ontology Language adds considerable expressive power to the Semantic Web it does have expressive limitations, particularly with respect to what can be said about properties. We present the Semantic Web Rule Language (SWRL), a Horn ...
Generating OWL Ontology for Database Integration
SEMAPRO '09: Proceedings of the 2009 Third International Conference on Advances in Semantic ProcessingToday, databases provide the best technique for storing and retrieving data, but they suffer from the absence of a semantic perspective, which is needed to reach global goals such as the semantic web and data integration. Using ontologies will solve ...
Re-engineering OntoSem Ontology Towards OWL DL Compliance
Proceedings of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software EngineeringRe-engineering of successful pre-OWL ontologies or other formal ER or UML system models towards OWL DL compliance opens new possibilities in ontology debugging, enabled by the formal semantics and automated reasoners developed for OWL DL. Meanwhile the ...
Comments