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

Andon Tchechmedjiev,Soumia Melzi,Clement Jonquet,Jitendra Jonnagaddala,Vincent Emonet,Amine Abdaoui

doi:10.1093/bioinformatics/bty009

Abstract

SummarySecond 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).Availability and implementationThe 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 available, 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).Supplementary information Supplementary data are available at Bioinformatics online.

Highlights

Semantic annotation of clinical data with standard medical terminologies/ontologies facilitates second use and translational data discoveries
In the context of the Semantic Indexing of French biomedical Resources (SIFR) project, in which we have developed a French version of the Annotator, we have implemented some new features for French that we seamlessly ported to English through a proxy Web service called NCBO Annotatorþ
We briefly report on the performance of the NCBO Annotatorþ for: (i) annotating and contextualizing concepts in clinical text on the CLEF eHealth 2017 task 1 corpus (Neveol et al, 2017), created for the automatic annotation of death certificates with ICD-10 codes; (ii) the SemEval 2015 Task 14.2 development corpus, created for the identification of biomedical concepts and of clinical context features

Summary

Introduction

Semantic annotation of clinical data with standard medical terminologies/ontologies facilitates second use and translational data discoveries. Researchers have developed systems to automatically detect clinical conditions and extract valuable knowledge in order to facilitate decision support (Rothman et al, 2012), VC The Author(s) 2018.

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Results

Conclusion