2004
DOI: 10.1111/j.1471-1842.2004.00526.x
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Enhancing the MeSH thesaurus to retrieve French online health resources in a quality‐controlled gateway

Abstract: The amount of health information available on the Internet is considerable.

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Cited by 33 publications
(27 citation statements)
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“…However, the literature is quite sparse in the medical domain, which is a distinct problem, because of the complexity of medical vocabularies. In this section, a simple method is proposed: it combines two approximate string comparators, the well-known Levenshtein [6] edit distance and the Stoilos function similarity defined in [26] for ontologies. We apply and evaluate these two distances, alone and combined, on a set of sample queries in French submitted to the health gateway CISMeF.…”
Section: Proposed Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…However, the literature is quite sparse in the medical domain, which is a distinct problem, because of the complexity of medical vocabularies. In this section, a simple method is proposed: it combines two approximate string comparators, the well-known Levenshtein [6] edit distance and the Stoilos function similarity defined in [26] for ontologies. We apply and evaluate these two distances, alone and combined, on a set of sample queries in French submitted to the health gateway CISMeF.…”
Section: Proposed Methodsmentioning
confidence: 99%
“…Many ways of navigation and information retrieval are possible in the catalogue [6]. The most used is the simple search (free text interface).…”
Section: Searching Through the Cataloguementioning
confidence: 99%
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“…Originally developed for indexing of MEDLINE [13][14], it is presently in use in many search systems including various library catalogues, CISMeF [15], Euroethics [16] and SveMed+. The MeSH has been translated into several languages [3,17], making it suitable as the basis of multilingual search tools in the medical field [15,18]. For example, the Swedish MeSH is available as a browsing tool 2 .…”
Section: The Meshmentioning
confidence: 99%
“…• The UMLS Knowledge Sources (databases) integrates over 2 million names for some 900,000 concepts from over 154 biomedical vocabularies from 60 families of vocabularies, as well as 12 million relations between these concepts used in patient records, administrative data, full-text databases and expert systems (Bodenreider, 2004 The HMTP includes also a CISMeF thesaurus (Douyère et al, 2004), which is an extension to the MeSH thesaurus, includes 130 metaterms (super-concepts to unify MeSH terms of the same medical discipline), 300 resource types (adaptation to the Internet of the publication types), over 200 predefined queries and the translation of 12,000 MeSH Scope Notes (8,000 manually and the rest semi-automatically). To fit all the terminologies into one global structure and allow semantic interoperability, a generic model compliant with the terminology ISO model was designed.…”
Section: The Unified Medical Language System (Umls) Projectmentioning
confidence: 99%