Mapping biomedical terminologies using natural language processing tools and UMLS: Mapping the Orphanet thesaurus to the MeSH

Merabti, Tayeb; Joubert, Michel; Lecroq, Thierry; Rath, Ana; Darmoni, Stéfan Jacques

doi:10.1016/j.irbm.2010.04.003

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…Each approach can be improved: UMLS-based approach could benefit from additional French terminologies added to the UMLS Metathesaurus or more integrated terminologies translated in French. Due to this problem we proposed multiple approaches to map several French terminologies not integrated in the UMLS to the UMLS such as the Classification Commune des Actes Médicaux (CCAM)"A French coding system of surgical procedures" [ 17 ] and the ORPHANET database of rare diseases [ 35 ]. For the lexical approach, several improvements can be proposed to resolve problems due to the management of ambiguous acronyms across terminologies ( e.g .…”

Section: Discussionmentioning

confidence: 99%

“…When a correspondence was found, the translation of the English target term was proposed as one possible translation of the FMA term. This algorithm was exploited in several previously reported studies to map external French and English terminologies to UMLS and HMTP [ 17 , 34 , 35 ]. In this method, we used some Natural Language Processing tools developed by the NLM ® [ 36 ].…”

Section: Methodsmentioning

confidence: 99%

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Translating the foundational model of anatomy into french using knowledge-based and lexical methods

Merabti

Soualmia

Grosjean

et al. 2011

BMC Med Inform Decis Mak

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BackgroundThe Foundational Model of Anatomy (FMA) is the reference ontology regarding human anatomy. FMA vocabulary was integrated into the Health Multi Terminological Portal (HMTP) developed by CISMeF based on the CISMeF Information System which also includes 26 other terminologies and controlled vocabularies, mainly in French. However, FMA is primarily in English. In this context, the translation of FMA English terms into French could also be useful for searching and indexing French anatomy resources. Various studies have investigated automatic methods to assist the translation of medical terminologies or create multilingual medical vocabularies. The goal of this study was to facilitate the translation of FMA vocabulary into French.MethodsWe compare two types of approaches to translate the FMA terms into French. The first one is UMLS-based on the conceptual information of the UMLS metathesaurus. The second method is lexically-based on several Natural Language Processing (NLP) tools.ResultsThe UMLS-based approach produced a translation of 3,661 FMA terms into French whereas the lexical approach produced a translation of 3,129 FMA terms into French. A qualitative evaluation was made on 100 FMA terms translated by each method. For the UMLS-based approach, among the 100 translations, 52% were manually rated as "very good" and only 7% translations as "bad". For the lexical approach, among the 100 translations, 47% were rated as "very good" and 20% translations as "bad".ConclusionsOverall, a low rate of translations were demonstrated by the two methods. The two approaches permitted us to semi-automatically translate 3,776 FMA terms from English into French, this was to added to the existing 10,844 French FMA terms in the HMTP (4,436 FMA French terms and 6,408 FMA terms manually translated).

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Translating the foundational model of anatomy into french using knowledge-based and lexical methods

Merabti

Soualmia

Grosjean

et al. 2011

BMC Med Inform Decis Mak

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“…One of the authors (SJD) has created exact match mappings between MeSH, OMIM, HPO and HRDO based on a natural language processing/conceptual based algorithm [ 17 , 18 ] suggestions. Exact match mapping means that the two concepts are real synonyms (e.g.…”

Section: Methodsmentioning

confidence: 99%

Searching for rare diseases in PubMed: a blind comparison of Orphanet expert query and query based on terminological knowledge

Griffon

Schuers

Dhombres

et al. 2016

BMC Med Inform Decis Mak

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BackgroundDespite international initiatives like Orphanet, it remains difficult to find up-to-date information about rare diseases. The aim of this study is to propose an exhaustive set of queries for PubMed based on terminological knowledge and to evaluate it versus the queries based on expertise provided by the most frequently used resource in Europe: Orphanet.MethodsFour rare disease terminologies (MeSH, OMIM, HPO and HRDO) were manually mapped to each other permitting the automatic creation of expended terminological queries for rare diseases. For 30 rare diseases, 30 citations retrieved by Orphanet expert query and/or query based on terminological knowledge were assessed for relevance by two independent reviewers unaware of the query’s origin. An adjudication procedure was used to resolve any discrepancy. Precision, relative recall and F-measure were all computed.ResultsFor each Orphanet rare disease (n = 8982), there was a corresponding terminological query, in contrast with only 2284 queries provided by Orphanet. Only 553 citations were evaluated due to queries with 0 or only a few hits. There were no significant differences between the Orpha query and terminological query in terms of precision, respectively 0.61 vs 0.52 (p = 0.13). Nevertheless, terminological queries retrieved more citations more often than Orpha queries (0.57 vs. 0.33; p = 0.01). Interestingly, Orpha queries seemed to retrieve older citations than terminological queries (p < 0.0001).ConclusionThe terminological queries proposed in this study are now currently available for all rare diseases. They may be a useful tool for both precision or recall oriented literature search.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-016-0333-0) contains supplementary material, which is available to authorized users.

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“…This approach uses a French NLP tool and mapping algorithms developed by the CISMeF team to map French medical terminologies (Merabti, 2010;Merabti et al, 2010a;. These tools were initially developed in previous works for information retrieval (Soualmia, 2004) and extended to link terms in multiple French medical terminologies:…”

Section: Lexical Approach For Medical Terminologies In Frenchmentioning

confidence: 99%

Aligning Biomedical Terminologies in French: Towards Semantic Interoperability in Medical Applications

Merabti¹,

Soualmia²,

Grosjean³

et al. 2012

Medical Informatics

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Mapping biomedical terminologies using natural language processing tools and UMLS: Mapping the Orphanet thesaurus to the MeSH

Cited by 9 publications

References 5 publications

Translating the foundational model of anatomy into french using knowledge-based and lexical methods

Translating the foundational model of anatomy into french using knowledge-based and lexical methods

Searching for rare diseases in PubMed: a blind comparison of Orphanet expert query and query based on terminological knowledge

Aligning Biomedical Terminologies in French: Towards Semantic Interoperability in Medical Applications

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