Translating ICD-11 into French using lexical-based approach: a preliminary study.

To translate the 11th edition of the International Classification of Diseases (ICD-11) into French, we proposed a lexical approach using Natural Language Processing techniques. This method relies on the 56 biomedical terminologies and ontologies included in the Cross-lingual Health Multiple Terminologies and Ontologies Portal. From a sample of 336 ICD-11 terms, the algorithm translated 164 (49%) terms into at least one French term each.

InfoRoute: the CISMeF Context-specific Search Algorithm.

OBJECTIVE: The aim of this paper was to present a practical InfoRoute algorithm and applications developed by CISMeF to perform a contextual information retrieval across multiple medical websites in different health domains. METHODS: The algorithm was developed to treat multiple types of queries: natural, Boolean and advanced. The algorithm also generates multiple types of queries: Boolean query, PubMed query or Advanced query. Each query can be extended via an inter alignments relationship from UMLS and HeTOP portal. RESULTS: A web service and two web applications have been developed based on the InfoRoute algorithm to generate links-query across multiple websites, i.e.: "PubMed" or "ClinicalTrials.org". CONCLUSION: The InfoRoute algorithm is a useful tool to perform contextual information retrieval across multiple medical websites in both English and French.

Preservation of information in terminology transcoding.

Linking interface terminologies (IT) to reference terminologies (RT) in flow of terminologies may allow health information system to be both usable and interoperable. Two French university hospitals worked independently on such a flow from the prescription of lab-test to the display of the corresponding results. The aim of this study was to evaluate the transmission of information in these two hospitals communication. An expert, supported by natural language processing tool, created the gold standard link between the 2 prescription ITs i.e. the terms that share the same meaning. A semantic pathway was defined to allow the mapping of one prescription IT to the other, through LOINC® and SNOMED®, the RT chosen by each hospital, respectively. The capacity of the semantic pathway to identify the correct links was computed. The expert found 218 links between the 2 prescription ITs (containing 580 and 374 terms that are linked to RT). The semantic pathway correctly identifies 96 of these links (44.0% [37.4-50.6]). The recall was not as good as expected, even though the semantic pathway was created in order to maximize it. Using different RT in different hospitals is not an efficient solution. The use of LOINC® seems to be preferable as a RT for prescription.

Evaluating alignment quality between iconic language and reference terminologies using similarity metrics.

BACKGROUND: Visualization of Concepts in Medicine (VCM) is a compositional iconic language that aims to ease information retrieval in Electronic Health Records (EHR), clinical guidelines or other medical documents. Using VCM language in medical applications requires alignment with medical reference terminologies. Alignment from Medical Subject Headings (MeSH) thesaurus and International Classification of Diseases - tenth revision (ICD10) to VCM are presented here. This study aim was to evaluate alignment quality between VCM and other terminologies using different measures of inter-alignment agreement before integration in EHR. METHODS: For medical literature retrieval purposes and EHR browsing, the MeSH thesaurus and the ICD10, both organized hierarchically, were aligned to VCM language. Some MeSH to VCM alignments were performed automatically but others were performed manually and validated. ICD10 to VCM alignment was entirely manually performed. Inter-alignment agreement was assessed on ICD10 codes and MeSH descriptors, sharing the same Concept Unique Identifiers in the Unified Medical Language System (UMLS). Three metrics were used to compare two VCM icons: binary comparison, crude Dice Similarity Coefficient (DSCcrude), and semantic Dice Similarity Coefficient (DSCsemantic), based on Lin similarity. An analysis of discrepancies was performed. RESULTS: MeSH to VCM alignment resulted in 10,783 relations: 1,830 of which were manually performed and 8,953 were automatically inherited. ICD10 to VCM alignment led to 19,852 relations. UMLS gathered 1,887 alignments between ICD10 and MeSH. Only 1,606 of them were used for this study. Inter-alignment agreement using only validated MeSH to VCM alignment was 74.2% [70.5-78.0]CI95%, DSCcrude was 0.93 [0.91-0.94]CI95%, and DSCsemantic was 0.96 [0.95-0.96]CI95%. Discrepancy analysis revealed that even if two thirds of errors came from the reviewers, UMLS was nevertheless responsible for one third. CONCLUSIONS: This study has shown strong overall inter-alignment agreement between MeSH to VCM and ICD10 to VCM manual alignments. VCM icons have now been integrated into a guideline search engine (http://www.cismef.org) and a health terminologies portal (http://www.hetop.eu).

Integrating the human phenotype ontology into HeTOP terminology-ontology server.

The Human Phenotype Ontology (HPO) is a controlled vocabulary which provides phenotype data related to genes or diseases. The Health Terminology/Ontology Portal (HeTOP) is a tool dedicated to both human beings and computers to access and browse biomedical terminologies or ontologies (T/O). The objective of this work was to integrate the HPO into HeTOP in order to enhance both works. This integration is a success and allows users to search and browse the HPO with a dedicated interface. Furthermore, the HPO has been enhanced with the addition of content such as new synonyms, translations, mappings. Integrating T/O such as the HPO into HeTOP is a benefit to vocabularies because it allows enrichment of them and it is also a benefit for HeTOP which provides a better service to both humans and machines.

Translating MeSH concepts.

The concept-oriented structure of the MeSH® thesaurus is not yet in common use. Nevertheless, it has been shown that a concept-based querying of PubMed may be of interest. To take full advantage of the concept-oriented structure of MeSH in the information retrieval tool associated with the CISMeF catalogue, it was necessary to translate such concepts into French.

Assisting the translation of SNOMED CT into French.

The objective of this study is to evaluate to approaches assisting the translation of SNOMED CT into French. Two types of approaches were combined: a concept-based one, which relies on conceptual information of the UMLS Metathesaurus and a lexical-based one, which relieson NLP techniques. In addition to the French terminologies (whether included in UMLS or not). Using the concept-based approach, a set of 156,157 (39.4%) SNOMED CT terms were translated to at least one French term from UMLS. Expanded to the French terms from UMLS terminologies translated by CISMeF, 2,548 (+0.7%) additional SNOMED CT terms were translated to at least one French term. Using the lexical-based approach, a set of 145,737 (36.8%) SNOMED CT terms were translated to at least one French term from HeTOP. The qualitative evaluation showed that 44% of the translations were rated as "relevant". Overall, the two approaches have provided the translation of 168,750 (42.6%) SNOMED CT terms into French using different bilingual terminological sources included in UMLS or in HeTOP.

Method for mapping the French CCAM terminology to the UMLS metathesaurus.

The French coding system of surgical procedures, the Classification Commune des Actes Médicaux (CCAM), is used in France for DRG databases and fee for services payment. Mapping between CCAM and other clinical procedures terminologies by the means of UMLS metathesaurus is essential in order to increase semantic interoperability between different healthcare terminologies and between different case mix systems. In a previous work the CISMeF team used an automatic approach to map CCAM descriptors to the French part of the UMLS metathesaurus. In another way for the French funded research project InterSTIS, we performed a mapping using MetaMap based on the top level semantic structure descriptors of anatomy and action of CCAM translated from French to English. This paper aims to present this new approach and to compare the results with the previous one. The combination of both approaches significantly improved the coverage of the mapping to 68 % for both descriptors and 95 % for at least one descriptor.

Teaching medicine with a terminology/ontology portal.

UNLABELLED: The Health Terminology/Ontology Portal (HeTOP) was developed to provide easy access to health terminologies and ontologie. The repository is not only dedicated to professionals but is also a valuable teaching tool. Currently, it provides access to thirty two health terminologies and ontologies available mainly in French or in English, but also in German, Italian, Chinese, etc. HeTOP can be used by both humans and computers via Web services. To integrate new resources into HeTOP, three steps are necessary: (1) designing a meta-model into which each terminology (or ontology) can be integrated, (2) developing a process to include terminologies into HeTOP, (3) building and integrating existing and new inter & intra-terminology semantic harmonization into HeTOP. Currently, 600 unique machines use the MeSH version of HeTOP every day and restricted terminologies/ontologies are used for teaching purposes in several medical schools in France. The multilingual version of HeTOP is available (URL: http://hetop.eu/) and provides free access to ICD10 and FMA in ten languages. CONCLUSION: HeTOP is a rich tool, useful for a wide range of applications and users, especially in education and resource indexing but also in information retrieval or performing audits in terminology management.

Translating the Foundational Model of Anatomy into French using knowledge-based and lexical methods.

BACKGROUND: The 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. METHODS: We 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. RESULTS: The 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". CONCLUSIONS: Overall, 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).

Assisting the translation of the CORE subset of SNOMED CT into French.

BACKGROUND: the Core Subset of SNOMED CT is part of the UMLS-Core Project dedicated to study problem list vocabularies. SNOMED CT is not yet translated into French. OBJECTIVE: to propose an automated method to assist the translation of the CORE Subset of SNOMED CT into French. MATERIAL: the 2009 AA versions of the CORE Subset of SNOMED CT and UMLS; use of four French-language terminologies integrated into the UMLS Metathesaurus: SNOMED International, ICD10, MedDRA, and MeSH. METHOD: an exact mapping completed by a close mapping between preferred terms of the CORE Subset of SNOMED CT and those of the four terminologies. RESULTS: 89% of the preferred terms of the CORE Subset of SNOMED CT are mapped with at least one preferred term in one of the four terminologies. DISCUSSION: if needed, synonymous terms could be added by the means of synonyms in the terminologies; the proposed method is independent from French and could be applied to other natural languages.

Health multi-terminology portal: a semantic added-value for patient safety.

Since the mid-90s, several quality-controlled health gateways were developed. In France, CISMeF is the leading health gateway. It indexes Internet resources from the main institutions, using the MeSH thesaurus and the Dublin Core metadata element set. Since 2005, the CISMeF Information System (IS) includes 24 health terminologies, classifications and thesauri for indexing and information retrieval. This work aims at creating a Health Multi-Terminology Portal (HMTP) and connect it to the CISMeF Terminology Database mainly for searching concepts and terms among all the health controlled vocabularies available in French (or in English and translated in French) and browsing it dynamically. To integrate the terminologies in the CISMeF IS, three steps are necessary: (1) designing a meta-model into which each terminology can be integrated, (2) developing a process to include terminologies into the HMTP, (3) building and integrating existing and new inter-terminology mappings into the HMTP. A total of 24 terminologies are included in the HMTP, with 575,300 concepts, 852,000 synonyms, 222,800 definitions and 1,180,000 relations. Heightteen of these terminologies are not included yet in the UMLS among them, some from the World Health Organization. Since January 2010, HMTP is daily used by CISMeF librarians to index in multi-terminology mode. A health multiterminology portal is a valuable tool helping the indexing and the retrieval of resources from a quality-controlled patient safety gateway. It can also be very useful for teaching or performing audits in terminology management.

Mapping the ATC classification to the UMLS metathesaurus: some pragmatic applications.

ATC classification is a WHO international classification used to classify drugs. The aim of this paper is to evaluate two lexical methods in English and in French to map ATC to UMLS. Several applications have been impemented to illustrate the use of the ATC mapping in English and French: (a) MeSH translation in Norwegian, (b) Drug Information Portal, and (c) ATC to PubMed tool. Two lexical methods were used to map ATC to UMLS. The first approach used a French natural language processing tool to map French terms of ATC to the French terminologies of UMLS. The second approach used the MetaMap tool to map English terms of ATC to UMLS. The English MetaMap provides slightly more mappings than the French NLP tool (3,170 vs. 2,992). On the other hand, the French NLP tool provides a slightly better precision than MetaMap (88% vs. 86%). Using a manual mapping between ATC and MeSH, the union of the validated mappings between ATC and MeSH provides 2,824 mappings (68.7% of ATC codes of the fifth level). Lexical methods are powerful methods to map health terminologies to the UMLS Metathesaurus. Manual mapping is still necessary to complete the mapping.

An automated approach to map a French terminology to UMLS.

BACKGROUND: CCAM is a French terminology for coding clinical procedures. CCAM is a multi-hierarchical structured classification for procedures used in France for reimbursement in health care, which is external to UMLS. OBJECTIVE: The objective of this work is to describe a French lexical approach allowing mapping CCAM procedures to the UMLS Metathesaurus to achieve interoperability to multiple international terminologies. This approach used a preliminary step intended to take only the significant characters used to code CCAM corresponding to anatomical and actions axes. RESULTS: According to the 7,926 CCAM codes used in this study, 5,212 possible matches (exact matching, single to multiple matching, partial matching) are found using the French CCAM to UMLS based mapping, 65% of the corresponding anatomical terms in the CCAM code are mapped to at least one UMLS Concept and 37% of the corresponding action terms in the CCAM code are mapped to at least one UMLS Concept. For all the exact matches found (n=200), 91% were rated by a human expert as narrower than the mapped UMLS Concepts, while only 3% were irrelevant.

A twofold strategy for translating a medical terminology into French.

OBJECTIVE: The goal of this study is to assist the translation of a medical terminology (MedlinePlus) into French. METHODS: We combined two types of approaches to acquire French translations of English MedlinePlus terms. The first is knowledge-based and relies on the conceptual information of the UMLS metathesaurus. The second method is a corpus-based NLP technique using a bilingual parallel corpus. RESULTS: The knowledge-based method brought translations for 611 terms, among which 67.6% were considered valid. The corpus-based approach provided translations for 143 terms of which 71.3% were considered valid. We thus acquired a total of 435 translated terms (51.3%). CONCLUSION: Combining two approaches allowed us to semi-automatically translate more than half of the terminology, while focusing on only one would have provided a more partial translation. From an applicative viewpoint, this French version is now integrated in the catalogue of online health resources CISMeF.

Projection and inheritance of SNOMED CT relations between MeSH terms.

This paper proposes a methodology to achieve the automatic inheritance of SNOMED CT relations applied to MeSH preferred terms using UMLS as knowledge source server. We propose an interoperability wildcard to achieve this objective. A quantitative and a qualitative analysis were performed on top four SNOMED CT relations inherited between MeSH preferred terms. A total of 12,030 couples of MeSH preferred terms are in relation via at least one SNOMED CT relationship. For the top-four relations inherited between MeSH preferred terms, overall 79.25% of them are relevant, 16.25% as intermediate and 4.5% as irrelevant, as judged by a medical librarian. This work should lead to an optimization of multi-terminology indexing tools, multi-terminology information retrieval and navigation among a multi-terminology server.

Assisting the translation of SNOMED CT into French using UMLS and four representative French-language terminologies.

OBJECTIVE: To provide a semantics-based method to assist the translation of SNOMED CT into French. To do so, we selected four French-language terminologies: ICD-10, SNOMED International, MedDRA, MeSH, as they are dedicated to different uses - epidemiology, clinical medicine, adverse reactions, medical literature, respectively - in order to map them to SNOMED Clinical Terms (CT), and thus associate French terms with SNOMED CT concepts. In this way, we measured the number of SNOMED CT concepts to be found in French-language terminologies. MATERIAL AND METHOD: We used the UMLS Metathesaurus. The mapping method was based on the coincidence of identifiers and on the explicit mappings present in the Metathesaurus. RESULTS: The study dealt exclusively with preferred terms (PTs) in the terminologies. The terminologies are mapped with varying success as regards PTs mapped to SNOMED terms (from 52% to 96%). Conversely, 45% of SNOMED CT terms are mapped by uniting the four terminologies. DISCUSSION: A more effective mapping technique than the current method is under consideration. CONCLUSION: The method presented will be refined. It could certainly provide useful assistance in the translation of SNOMED CT into French. Due to its general nature, it could be used to translate SNOMED CT into other languages than French.

Searching related resources in a quality controlled health gateway: a feasibility study.

OBJECTIVE: The neighbors of a document are those documents in a corpus that are most similar to it. The objective of this paper is to develop and evaluate the related resources algorithm (CISMeF-RRA) in the context of a quality-controlled health gateway on the Internet CISMeF. METHOD: CISMeF-RRA is inspired by the PubMed Related Citations Articles. CISMeF-RRA combines statistical distances with a semantic distance using MeSH terms/qualifiers. MATERIAL: In this feasibility study an evaluation was performed using 50 CISMeF resources randomly chosen. RESULTS: Overall, 49% of the related documents were ranked as relevant. CONCLUSION: if this feasibility study is confirmed by another evaluation of more resources, CISMeF-RRA will be implemented in the CISMeF catalog.