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A Simple Tool to Enrich Clinical Trial Data with Multiontology-Based Conceptual Tags

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Data Integration in the Life Sciences (DILS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10649))

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Abstract

The use of ontologies to ease planning and execution of clinical trials and the handling of the resulting data has been proposed in various forms over the past years ranging from dedicated ontologies to ontology-driven software.

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References

  1. Apache Software Foundation: Lucene. https://lucene.apache.org

  2. Brochhausen, M., Weiler, G., Cocos, C., et al.: The ACGT master ontology on cancer - a new terminol. source for oncolog. Practice. In: Proceedings of IEEE Symposium on Computer-Based Medical Systems (2008)

    Google Scholar 

  3. CDISC Consortium: Operational Data Model (ODM). https://www.cdisc.org/odm

  4. DCMI: Dublin Core Meta. Elem. Set. http://dublincore.org/documents/dces

  5. Doods, J., Neuhaus, P., Dugas, M.: Converting ODM metadata to FHIR questionnaire resources. Stud. Health Technol. Inform. 228, 456–460 (2016)

    Google Scholar 

  6. Gearon, P., et al.: SPARQL Update. https://www.w3.org/TR/sparql11-update

  7. Leroux, H., Metke-Jimenez, A., Lawley, M.: ODM on FHIR: towards achieving semantic interoperability of clinical study data. In: Proceedings of SWAT4LS (2015)

    Google Scholar 

  8. National Cancer Institute: NCI Thesaurus. https://ncit.nci.nih.gov

  9. Sanfilippo, E., Schwarz, U., Schneider, L.: The health data ontology trunk (HDOT) - towards an ontolog. represent. of cancer-related knowledge. In: Proceedings of IARWISOCI (2012)

    Google Scholar 

  10. SNOMED International: SNOMED CT. http://www.snomed.org/snomed-ct

  11. Stenzhorn, H., Weiler, G., Brochhausen, M., Schera, F., Kritsotakis, V., et al.: The ObTiMA system - ontology-based managing of clinical trials. In: Proceedings of Medinfo (2010)

    Google Scholar 

  12. FHIR IS WG. FHIR RDF Representation. https://www.hl7.org/fhir/rdf.html

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Correspondence to Holger Stenzhorn .

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Stenzhorn, H. (2017). A Simple Tool to Enrich Clinical Trial Data with Multiontology-Based Conceptual Tags. In: Da Silveira, M., Pruski, C., Schneider, R. (eds) Data Integration in the Life Sciences. DILS 2017. Lecture Notes in Computer Science(), vol 10649. Springer, Cham. https://doi.org/10.1007/978-3-319-69751-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-69751-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69750-5

  • Online ISBN: 978-3-319-69751-2

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