InfoRoute: the CISMeF Context-specific Search Algorithm

International audienceThe 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

InfoRoute: the CISMeF Context-specific Search Algorithm

International audienceThe 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

Inheritance of SNOMED CT Relations between Concepts by two Health Terminologies (SNOMED International and ICD-10)

Poster at KR-MED 2008 - Representing and sharing knowledge using SNOMED International Conference, Phoenix, AZ, US

Keyword Search in Heterogeneous Data Sources

Data journalism is the field of investigative journalism work based first and foremost on digital data. As more and more of human activity leaves strong digital traces, data journalism is an increasingly important trend. Important journalism projects increasingly involve diverse data sources, having heterogeneous data models, different structures, or no structure at all; the Offshore Leaks is a prime example. Inspired by our collaboration with Le Monde, a leading French newspaper , we designed a novel content management architecture, together with an algorithm for exploiting such heterogeneous corpora through keyword search: given a set of search terms, find links between them within and across the different datasets which we interconnect in a graph. Our work recalls keyword search in structured and unstructured data, but data heterogeneity makes it computationally harder. We analyze the performance of our algorithm on real-life datasets

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

Mapping biomedical terminologies using natural language processing tools and umls : mapping the orphanet thesaurus to the mesh

National audienc