Andon Tchechmedjiev1,2, Amine Abdaoui3, Vincent Emonet3, Stella Zevio3, Clement Jonquet3,4. 1. Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM), University of Montpellier, CNRS, 161, rue Ada, 34095, Montpellier cedex 5, France. andon.tchechmedjiev@lirmm.fr. 2. LGI2P, IMT Mines Ales, Univ Montpellier, Alès, France. andon.tchechmedjiev@lirmm.fr. 3. Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM), University of Montpellier, CNRS, 161, rue Ada, 34095, Montpellier cedex 5, France. 4. Center for Biomedical Informatics Research (BMIR), Stanford University, 1265 Welch Rd, Stanford, CA, 94305, USA.
Abstract
BACKGROUND: Despite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ontologies are only available in English, and cannot be readily applied to other languages, due to fundamental linguistic differences. However, semantic resources are required to design semantic indexes and transform biomedical (text)data into knowledge for better information mining and retrieval. RESULTS: We present the SIFR Annotator ( http://bioportal.lirmm.fr/annotator ), a publicly accessible ontology-based annotation web service to process biomedical text data in French. The service, developed during the Semantic Indexing of French Biomedical Data Resources (2013-2019) project is included in the SIFR BioPortal, an open platform to host French biomedical ontologies and terminologies based on the technology developed by the US National Center for Biomedical Ontology. The portal facilitates use and fostering of ontologies by offering a set of services -search, mappings, metadata, versioning, visualization, recommendation- including for annotation purposes. We introduce the adaptations and improvements made in applying the technology to French as well as a number of language independent additional features -implemented by means of a proxy architecture- in particular annotation scoring and clinical context detection. We evaluate the performance of the SIFR Annotator on different biomedical data, using available French corpora -Quaero (titles from French MEDLINE abstracts and EMEA drug labels) and CépiDC (ICD-10 coding of death certificates)- and discuss our results with respect to the CLEF eHealth information extraction tasks. CONCLUSIONS: We show the web service performs comparably to other knowledge-based annotation approaches in recognizing entities in biomedical text and reach state-of-the-art levels in clinical context detection (negation, experiencer, temporality). Additionally, the SIFR Annotator is the first openly web accessible tool to annotate and contextualize French biomedical text with ontology concepts leveraging a dictionary currently made of 28 terminologies and ontologies and 333 K concepts. The code is openly available, and we also provide a Docker packaging for easy local deployment to process sensitive (e.g., clinical) data in-house ( https://github.com/sifrproject ).
BACKGROUND: Despite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ontologies are only available in English, and cannot be readily applied to other languages, due to fundamental linguistic differences. However, semantic resources are required to design semantic indexes and transform biomedical (text)data into knowledge for better information mining and retrieval. r> RESULTS: We present the SIFR Annotator ( http://bioportal.lirmm.fr/annotator ), a publicly accessible ontology-based annotation web service to process biomedical text data in French. The service, developed during the Semantic Indexing of French Biomedical Data Resources (2013-2019) project is included in the SIFR BioPortal, an open platform to host French biomedical ontologies and terminologies based on the technology developed by the US National Center for Biomedical Ontology. The portal facilitates use and fostering of ontologies by offering a set of services -search, mappings, metadata, versioning, visualization, recommendation- including for annotation purposes. We introduce the adaptations and improvements made in applying the technology to French as well as a number of language independent additional features -implemented by means of a proxy architecture- in particular annotation scoring and clinical context detection. We evaluate the performance of the SIFR Annotator on different biomedical data, using available French corpora -Quaero (titles from French MEDLINE abstracts and EMEA drug labels) and CépiDC (ICD-10 coding of death certificates)- and discuss ourresults with respect to the CLEF eHealth information extraction tasks. r> CONCLUSIONS: We show the web service performs comparably to other knowledge-based annotation approaches in recognizing entities in biomedical text and reach state-of-the-art levels in clinical context detection (negation, experiencer, temporality). Additionally, the SIFR Annotator is the first openly web accessible tool to annotate and contextualize French biomedical text with ontology concepts leveraging a dictionary currently made of 28 terminologies and ontologies and 333 K concepts. The code is openly available, and we also provide a Docker packaging for easy local deployment to process sensitive (e.g., clinical) data in-house ( https://github.com/sifrproject ).
Authors: S J Darmoni; E Jarrousse; P Zweigenbaum; P Le Beux; F Namer; R Baud; M Joubert; H Vallée; R A Côté; A Buemi; D Bourigault; G Recource; S Jeanneau; J M Rodrigues Journal: AMIA Annu Symp Proc Date: 2003
Authors: Nigam H Shah; Nipun Bhatia; Clement Jonquet; Daniel Rubin; Annie P Chiang; Mark A Musen Journal: BMC Bioinformatics Date: 2009-09-17 Impact factor: 3.169
Authors: Nigam H Shah; Clement Jonquet; Annie P Chiang; Atul J Butte; Rong Chen; Mark A Musen Journal: BMC Bioinformatics Date: 2009-02-05 Impact factor: 3.169