Enhanced functionalities for annotating and indexing clinical text with the NCBO Annotator.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

SUMMARY: Second use of clinical data commonly involves annotating biomedical text with terminologies and ontologies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally designed for biomedical data, but not very suitable for clinical text annotation. In order to add new functionalities to the NCBO Annotator without hosting or modifying the original Web service, we have designed a proxy architecture that enables seamless extensions by pre-processing of the input text and parameters, and post processing of the annotations. We have then implemented enhanced functionalities for annotating and indexing free text such as: scoring, detection of context (negation, experiencer, temporality), new output formats and coarse-grained concept recognition (with UMLS Semantic Groups). In this paper, we present the NCBO Annotator+, a Web service which incorporates these new functionalities as well as a small set of evaluation results for concept recognition and clinical context detection on two standard evaluation tasks (Clef eHealth 2017, SemEval 2014).

Authors

  • Andon Tchechmedjiev
    Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM), University of Montpellier & CNRS, Montpellier 34090, France.
  • Amine Abdaoui
    LIRMM, 860 St Priest Street, 34095 Montpellier, France.
  • Vincent Emonet
    Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM), University of Montpellier & CNRS, Montpellier 34090, France.
  • Soumia Melzi
    Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM), University of Montpellier & CNRS, Montpellier 34090, France.
  • Jitendra Jonnagaddala
    School of Public Health and Community Medicine, University of New South Wales, Australia; Asia-Pacific Ubiquitous Healthcare Research Centre, University of New South Wales, Australia; Prince of Wales Clinical School, University of New South Wales, Australia.
  • Clement Jonquet
    Stanford Center for Biomedical Informatics Research, 1265 Welch Road, Stanford University School of Medicine, Stanford, CA, 94305-5479, USA.