Search

International audience; Health professionals are faced with challenges when they have to exploit the semantics of concepts present in clinical terminologies in support of research activities. The difficulty lies in the fact that this semantics is represented not only through the labels of concepts, but also their position in the hierarchy, and, when available, their logical and textual definitions. We investigate and contrast the lexical, hierarchical, and logical representations of concepts in SNOMED CT through the example of Anemia and three other disorders. The four use cases we developed suggest that the lexical, hierarchical, and logical representations of concepts have a limited degree of overlap, but are complementary. Finally, we draw practical implications from our findings for SNOMED CT users and developers.

International audience

International audience; Linkages between animal models of diseases and human data enable the development of translational research hypotheses. The objective of this study is to investigate two approaches to integrating phenotype and clinical information. On the one hand, we develop a terminology mapping between phenotypes from the Mammalian Phenotype Ontology (MPO) and Online Mendelian Inheritance in Man (OMIM) through the Unified Medical Language System (UMLS). On the other, we associate MPO phenotypes with OMIM manifestations through annotations made to orthologous genes. 1,469 MPO concepts (22%) were mapped successfully to some disease concept in the UMLS, of which 869 were present in OMIM. Among the 16,764 distinct MGI genes associated with human orthologs, 1,968 distinct genes were associated with both MPO and OMIM annotations. The UMLS is a valuable resource for linking phenotype terms to clinical terminologies, and these mappings between terminologies can help enrich gene annotation databases and unify phenotype representation.

International audience; Auditing biomedical terminologies often results in the identification of inconsistencies and thus helps to improve their quality. In this paper, we present a method based on Semantic Web technologies for auditing biomedical terminologies and apply it to the NCI thesaurus. We stored the NCI thesaurus concepts and their properties in an RDF triple store. By querying this store, we assessed the consistency of both hierarchical and associative relations from the NCI thesaurus among themselves and with corresponding relations in the UMLS Semantic Network. We show that the consistency is better for associative relations than for hierarchical relations. Causes for inconsistency and benefits from using Semantic Web technologies for auditing purposes are discussed.

A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature.

International audience; Each biomedical system has its own way of naming the pieces of information it contains, i.e., of defining its data elements (DEs). Integrating DEs facilitates the integration of biomedical resources. However, the mapping of DEs to the UMLS is ambiguous in many cases, when any correspondence is found at all. We propose to evaluate the potential contribution of a more general terminology: WordNet. Our method is based on synonyms, definitions, and structural properties of the terminologies. We applied it to a set of 474 DEs extracted from eleven biomedical sources. We show that WordNet can improve the direct mapping of DEs to UMLS when used to validate and disambiguate UMLS direct mappings. WordNet can also help identify indirect mappings of DEs to the UMLS.

International audience; Applications exploiting the hierarchical relations recorded in the Unified Medical Language System (UMLS) Metathesaurus suffer from the presence of inconsistencies in these relations. A formal approach to identifying and eliminating circular hierarchical relations has been proposed in previous work, leading to the creation of a directed acyclic Metathesaurus graph. However, this approach is at best semi-automatic and its implementation is far from trivial. A simpler, alternative approach consists in avoiding loops while traversing the Metathesaurus graph by preventing nodes from being visited twice. Our objective is to evaluate the benefit of the formal approach to eliminating cycles over a naïve approach to avoiding them. To this end, we compared the size and semantic coherence of sets of descendants obtained by both approaches. 12% of the concepts with descendants exhibit some differences. The formal approach significantly reduces the number of descendants in these cases. The benefits in terms of semantic coherence are more subtle.

Integration of disparate biomedical terminologies is becoming increasingly important as links between biological science and clinical medicine grow. Mapping concepts in the Gene OntologyTM(GO) to the UMLS may help further this integration and allow for more efficient information exchange among researchers. Using a gold standard of GO term – UMLS concept mappings provided by the NCI, we examined the performance of various published and combined mapping techniques, in order to maximize precision and recall. We found that for the previously published techniques precision varied between (0.61–0.95), and recall varied from (0.65–0.90), whereas for the hybrid techniques, precision varied between (0.66–0.97), and recall from (0.59–0.93). Our study reveals the benefits of using mapping techniques that incorporate domain knowledge, and provides a basis for future approaches to mapping between distinct biomedical vocabularies.

In this study, we analyzed the compatibility between an ontology of the biomedical domain (the UMLS Semantic Network) and two other ontologies: the Upper Cyc Ontology (UCO) and WordNet. 1) We manually mapped UMLS Semantic Types to UCO. One fifth of the UMLS Semantic Types had exact mapping to UCO types. UCO provides generic concepts and a structure that relies on a larger number of categories, despite its lack of depth in the biomedical domain. 2) We compared semantic classes in the UMLS and WordNet. 2% of the UMLS concepts from the Health Disorder class were present in WordNet, and compatibility between classes was 48%. WordNet, as a general language-oriented ontology is a source of lay knowledge, particularly important for consumer health applications.

We introduce a new method to find semantic inconsistencies (i.e., concepts with erroneous synonymity) in the Unified Medical Language System (UMLS). The idea is to identify the inconsistencies by comparing the semantic groups of hierarchically-related concepts using Answer Set Programming. With this method, we identified several inconsistent concepts in UMLS and discovered an interesting semantic pattern along hierarchies, which seems associated with wrong synonymy.

The creation of regional standardized medical information databases in relation with the French anonymous discharge dataset allows the study of the geriatric case mix processed in the Lorraine region for patients over 69. The age histogram (69 to 107 years) presents a two mode distribution with an important dip centered on 79 years probably in connection with the demography of Lorraine and the consequences of the First World War. These geriatric patients represent 17% of hospitalisations in public and private hospitals participating in the public sector. The case mix is related to the size of the hospital and to its juridical status. The bigger the size of an hospital, the less its activity is concentrated on a small number of disorders. Lung and heart diseases represent the first cause of hospitalisation in all hospitals. It is necessary to underline the limitation of an approach which uses the patients' individual hospitalisations, and which does not allow different stays of a given patient on the same hospital or between different hospitals to be linked. This approach prevents from appreciating the care network for this elderly population suffering from chronic diseases.

Communication faite lors du Troisième colloque Hypermédias et Apprentissages et publié dans les actes (p. 281-292); Ce travail présente un bref rappel sur les environnements de développement multimédia habituellement utilisés dans le développement des applications pédagogiques (multimédia intégré), puis expose le principe de fonctionnement d'applications développées sur Internet dans une architecture world-wide web ou WWW (multimédia réparti). Les modalités du passage du multimédia intégré au multimédia réparti sont discutées, en prenant en compte les avantages (principalement la facilité de diffusion) et les contraintes et limites de cette migration, dans l'état actuel de développement d'Internet et des outils WWW, puis en anticipant sur les évolutions à venir. Enfin, quel que soit l'environnement utilisé, les auteurs insistent sur la nécessité d'utiliser une méthode de développement.

Anatomy is a major organizing principle for diseases. In the formal definitions provided by SNOMED CT, for example, the role ‘finding site’ relates disorders to anatomical entities. This study investigates SNOMED CT and compares the anatomy-based classification of diseases supported by the role finding site to the anatomy-based classification of diseases provided by subsumption (is-a) relations between diseases. For each of the 3,540 anatomical entities associated with disorders, we compared two sets of disorders: first, the set of disorders associated with any descendant of the anatomical entity under investigation (ANAT); second, the set of disorders corresponding to the union of the descendants of the disorders associated with the anatomical entity under investigation (TAXO). The ANAT and TAXO sets were different for 1,231 anatomical entities (35%). In 607 cases, the overlap between ANAT and TAXO was less than 50%. When a difference was found, the TAXO set was always a subset of the ANAT set. Among the 1,025,904 subsumption relations among disorders generated by the ANAT approach, 40% were not present in TAXO. This approach helps identify missing classes and taxonomic relations and can therefore be used for quality assurance purposes in existing ontologies. It can be generalized to other kinds of partitions of biomedical ontologies.