Ontology-driven Vaccination Information Extraction

Liliana Ferreira, António Teixeira, João Paulo Silva Cunha

2008

Abstract

Increasingly, medical institutions have access to clinical information through computers. The need to process and manage the large amount of data is motivating the recent interest in semantic approaches. Data regarding vaccination records is a common in such systems. Also, being vaccination is a major area of concern in health policies, numerous information is available in the form of clinical guidelines. However, the information in these guidelines may be difficult to access and apply to a specific patient during consultation. The creation of computer interpretable representations allows the development of clinical decision support systems, improving patient care with the reduction of medical errors, increased safety and satisfaction. This paper describes the method used to model and populate a vaccination ontology and the system which recognizes vaccination information on medical texts.The system identifies relevant entities on medical texts and populates an ontology with new instances of classes. An approach to automatically extract information regarding inter-class relationships using association rule mining is suggested.

References

  1. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. 20th International Conference Very Large Data Bases, VLDB, 1215: 487-499, 1994
  2. Cunha, J.P.C., Cruz, I., Oliveira, I., Pereira, A.S., Costa, C.T., Oliveira, A.M., Pereira, A.: The RTS project: Promoting secure and effective clinical telematic communication within the Aveiro region. In eHealth 2006 High Level Conference . Malaga, ES, Maio 2006 . p. 1-10
  3. Cunningham, H., Maynard, D., Bontcheva, K. , Tablan, V., and Ursu, C.: The GATE User Guide. 2002 http://gate.ac.uk/.
  4. Cunningham, H., Maynard, D., Bontcheva, K. , Tablan, V.: GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications. Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics (ACL'02). Philadelphia, July 2002
  5. Direca˜o Geral da Saú de Programa Nacional de Vacina ca˜o 2006, Orientao˜ es Técnicas No 10 2006
  6. Ferreira, L., Teixeira, A., Cunha, J.P.S.: Information Extraction from Medical Reports. In 3rd International Workshop on Natural Language Understanding and Cognitive Science (NLUCS2006), Paphos, Cyprus, May 2006.
  7. Herman, T.D., Liu, F., Sagaram, D., Raoul, K., Fontelo, P., Kohl, K., Payne, D.: Creating a vaccine adverse event ontology for public health. AMIA Annu Symp Proc. 2005, 978
  8. Horrocks, I, Patel-Schneider, P.F., Boley, H., Tabet, S, Grosof, B., Dean, M.: SWRL: A Semantic Web Rule Language - Combining OWL and RuleML. W3C Member Submission, http://www.w3.org/Submission/SWRL/, May 2004.
  9. Lassila, O., Swick, R.R.: Resource Description Framework (RDF) Model and Syntax. W3C Working Draft, World Wide Web Consortium, 1998; http://www.w3.org/TR/WD-rdf-syntax/.
  10. Liu, B., Hsu, W., Ma, Y.: Integrating Classification and Association Rule Mining. KDD-98, 1998
  11. McGuinness, D. L., Harmelen, F. , eds. OWL Web Ontology Language Overview. W3C Proposed Recommendation, December 2003, http://www.w3.org/TR/owl-features/.
  12. Sager, N., Lyman, M., Bucknall, C., Nhan, L.J., Tick, L.J.: Natural language processing and the representation of clinical data. J. Am. Med. Informatics Assoc. March, 1994, 1(2): 142-60.
  13. Serban, R., Teije, A., Harmelen, F., Marcos, M., Polo-Conde, C.: Extraction and use of linguistic patterns for modelling medical guidelines. Artif. Intell. Med Journal, 2007, 39:137-149
  14. Schrö der, M.: Knowledge-based processing of medical language: A language engineering approach. Proceeding of GWAI'92, Bonn, September 1992
  15. Sheth, A. P., Agrawal S., Lathem J., Oldham N., Wingate H., Yadav P., Gallagher K.: Active Semantic Electronic Medical Record. International Semantic Web Conference 2006: 913-926
  16. SNOMED Clinical Terms Guide. College of American Pathologists.
  17. UMLS KNOWLEDGE SOURCES. 14th Edition. National Institutes of Health Department of Health and Human Services. U.S. National Library of Medicine.
Download


Paper Citation


in Harvard Style

Ferreira L., Teixeira A. and Paulo Silva Cunha J. (2008). Ontology-driven Vaccination Information Extraction . In Proceedings of the 5th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2008) ISBN 978-989-8111-45-6, pages 94-103. DOI: 10.5220/0001739500940103


in Bibtex Style

@conference{nlpcs08,
author={Liliana Ferreira and António Teixeira and João Paulo Silva Cunha},
title={Ontology-driven Vaccination Information Extraction},
booktitle={Proceedings of the 5th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2008)},
year={2008},
pages={94-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001739500940103},
isbn={978-989-8111-45-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2008)
TI - Ontology-driven Vaccination Information Extraction
SN - 978-989-8111-45-6
AU - Ferreira L.
AU - Teixeira A.
AU - Paulo Silva Cunha J.
PY - 2008
SP - 94
EP - 103
DO - 10.5220/0001739500940103