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A Public Health Surveillance Platform Exploiting Free-Text Sources via Natural Language Processing and Linked Data: Application in Adverse Drug Reaction Signal Detection Using PubMed and Twitter

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Knowledge Representation for Health Care (ProHealth 2016, KR4HC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10096))

Abstract

This paper presents a platform enabling the systematic exploitation of diverse, free-text data sources for public health surveillance applications. The platform relies on Natural Language Processing (NLP) and a micro-services architecture, utilizing Linked Data as a data representational formalism. In order to perform NLP in an extendable and modular fashion, the proposed platform employs the Apache Unstructured Information Management Architecture (UIMA) and semantically annotates the results through a newly developed UIMA Semantic Common Analysis Structure Consumer (SCC). The SCC output is a graph represented in the Resource Description Framework (RDF) based on the W3C Web Annotation Data Model (WADM) and SNOMED-CT. We also present the use of the proposed platform through an exemplar application scenario concerning the detection of adverse drug reaction (ADR) signals using data retrieved from PubMed and Twitter.

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Notes

  1. 1.

    https://www.ibm.com/blogs/research/2011/04/open-architecture-helps-watson-understand-natural-language/.

  2. 2.

    https://www.ncbi.nlm.nih.gov/pubmed/.

  3. 3.

    https://twitter.com/?lang=en.

  4. 4.

    https://www.w3.org/RDF/.

  5. 5.

    http://www.hermit-reasoner.com/.

  6. 6.

    http://www.w3.org/TR/annotation-model/.

  7. 7.

    http://www.ihtsdo.org/snomed-ct.

  8. 8.

    http://europepmc.org/RestfulWebService.

  9. 9.

    https://dev.twitter.com/streaming/overview.

  10. 10.

    http://lucene.apache.org/solr/.

  11. 11.

    http://virtuoso.openlinksw.com/.

  12. 12.

    https://www.w3.org/TR/sparql11-http-rdf-update/.

  13. 13.

    http://www.nlm.nih.gov/research/umls/.

  14. 14.

    https://jena.apache.org/.

  15. 15.

    http://www.drugbank.ca/.

  16. 16.

    http://bio2rdf.org/.

  17. 17.

    https://uima.apache.org/downloads/sandbox/RDF_CC/RDFCASConsumerUserGuide.html.

  18. 18.

    https://www.mongodb.com/.

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Authors and Affiliations

  1. Lab of Computing and Medical Informatics, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Pantelis Natsiavas, Nicos Maglaveras & Vassilis Koutkias

  2. Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thermi, Thessaloniki, Greece

    Pantelis Natsiavas, Nicos Maglaveras & Vassilis Koutkias

Authors
  1. Pantelis Natsiavas
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  2. Nicos Maglaveras
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  3. Vassilis Koutkias
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Correspondence to Pantelis Natsiavas .

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Editors and Affiliations

  1. Rovira i Virgili University, Tarragona, Spain

    David Riaño

  2. University of Erlangen and Nuremberg, Erlangen, Germany

    Richard Lenz

  3. University of Ulm, Ulm, Germany

    Manfred Reichert

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Natsiavas, P., Maglaveras, N., Koutkias, V. (2017). A Public Health Surveillance Platform Exploiting Free-Text Sources via Natural Language Processing and Linked Data: Application in Adverse Drug Reaction Signal Detection Using PubMed and Twitter. In: Riaño, D., Lenz, R., Reichert, M. (eds) Knowledge Representation for Health Care. ProHealth KR4HC 2016 2016. Lecture Notes in Computer Science(), vol 10096. Springer, Cham. https://doi.org/10.1007/978-3-319-55014-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-55014-5_4

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