Enhanced Functionalities for Annotating and Indexing Clinical Text with the NCBO Annotator+ - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Bioinformatics Year : 2018

Enhanced Functionalities for Annotating and Indexing Clinical Text with the NCBO Annotator+

Abstract

Summary: Second use of clinical data commonly involves annotating biomedical text with terminologies and ontolo-gies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally de-signed 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 clini-cal context detection on two standard evaluation tasks (Clef eHealth 2017, SemEval 2014). Availability and Implementation: The Annotator+ has been successfully integrated into the SIFR BioPortal platform –an implementation of NCBO BioPortal for French biomedical terminologies and ontologies– to annotate English text. A Web user interface is available for testing and ontology selection (http://bioportal.lirmm.fr/ncbo_annotatorplus); however the Annotator+ is meant to be used through the Web service application programming interface (http://services.bioportal.lirmm.fr/ncbo_annotatorplus). The code is openly availa-ble, and we also provide a Docker packaging to enable easy local deployment to process sensitive (e.g., clinical) data in-house (https://github.com/sifrproject). Contact: andon.tchechmedjiev@lirmm.fr and jonquet@lirmm.fr Supplementary information: Technical details and documentation available online.
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lirmm-01680514 , version 1 (08-05-2018)

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Andon Tchechmedjiev, Amine Abdaoui, Vincent Emonet, Soumia Melzi, Jitendra Jonnagaddala, et al.. Enhanced Functionalities for Annotating and Indexing Clinical Text with the NCBO Annotator+. Bioinformatics, 2018, 34 (11), pp.1962-1965. ⟨10.1093/bioinformatics/bty009⟩. ⟨lirmm-01680514⟩
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