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Objectives: to rank according to their significance MeSH terms automatically extracted from Internet sites in the framework of a French project, VUMeF, a contribution to the NLM' UMLS project. Material and methods: scores are affected to key-words of a given document on the basis of the Semantic Network of the UMLS and frequencies of co-occurring major terms in the Medline literature. If N is the number of major terms of a document, and n is the number of major terms retrieved in the N first terms ranked in descending order according to their scores, the measure of the achievement of the method is n/N. Results: a set of 1444 randomized documents have been extracted from Medline. For each document we computed the retrieved major terms among the first N terms with two methods: a statistical method using only frequencies given by co-occurrences, and our method that uses furthermore the UMLS semantic network. In 34% of cases corresponding to documents indexed by about 16 key-words, about 3 major terms among them, our method produces a better precision (7%) than the statistical method. Discussion: the rough calculation of the proportion of retrieved major terms should be enhanced by the use of a probability law allowing to enlarge the list of terms to select taking into account both the number of major terms and the total number of key-words used to index each document. [ABSTRACT FROM AUTHOR]

The quality criteria of guidelines are identified. Taking these criteria into account we have built a platform to improve computable guideline effectiveness and facilitate their production. Our implementation is based on the GLIF Model (GuideLine Interchange Format). We have designed software components to edit, test, index, perform and present guidelines in a user-friendly Web architecture. These components are based on XML specifications in order to preserve their shareability and their re-usability. Several guidelines have been developed using our approach. We discuss the advantages of such an implementation and future evolutions so as to improve guideline integration within the clinician's workflow.