title: Improving information retrieval using Medical Subject Headings Concepts: a test case on rare and chronic diseases.
abstract: BACKGROUND
  As more scientific work is published, it is important to improve access to the biomedical literature. Since 2000, when Medical Subject Headings (MeSH) Concepts were introduced, the MeSH Thesaurus has been concept based. Nevertheless, information retrieval is still performed at the MeSH Descriptor or Supplementary Concept level.
  
  
  OBJECTIVE
  The study assesses the benefit of using MeSH Concepts for indexing and information retrieval.
  
  
  METHODS
  Three sets of queries were built for thirty-two rare diseases and twenty-two chronic diseases: (1) using PubMed Automatic Term Mapping (ATM), (2) using Catalog and Index of French-language Health Internet (CISMeF) ATM, and (3) extrapolating the MEDLINE citations that should be indexed with a MeSH Concept.
  
  
  RESULTS
  Type 3 queries retrieve significantly fewer results than type 1 or type 2 queries (about 18,000 citations versus 200,000 for rare diseases; about 300,000 citations versus 2,000,000 for chronic diseases). CISMeF ATM also provides better precision than PubMed ATM for both disease categories.
  
  
  CONCLUSIONS
  Using MeSH Concept indexing instead of ATM is theoretically possible to improve retrieval performance with the current indexing policy. However, using MeSH Concept information retrieval and indexing rules would be a fundamentally better approach. These modifications have already been implemented in the CISMeF search engine.
authors.affiliation: Catalogue et Index des Sites Médicaux de langue Française (CISMeF) and Traitement de l'Information en Biologie et Santé (TIBS), Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes (LITIS), Equipe d'Accueil (EA) 4108, Rouen University Hospital, 1 rue de Germont, 76031 Rouen Cedex, France. Stefan.Darmoni@chu-rouen.fr
authors.forename: Stéfan J
authors.initials: SJ
authors.lastname: Darmoni
authors.forename: Lina F
authors.initials: LF
authors.lastname: Soualmia
authors.forename: Catherine
authors.initials: C
authors.lastname: Letord
authors.forename: Marie-Christine
authors.initials: MC
authors.lastname: Jaulent
authors.forename: Nicolas
authors.initials: N
authors.lastname: Griffon
authors.forename: Benoît
authors.initials: B
authors.lastname: Thirion
authors.forename: Aurélie
authors.initials: A
authors.lastname: Névéol
mesh_terms: D000043:Abstracting and Indexing / Q000706:statistics & numerical data*; D000465:Algorithms; D002908:Chronic Disease; D019992:Databases as Topic / Q000706:statistics & numerical data*; D001330:Electronic Data Processing; D005602:France; D006801:Humans; D016247:Information Storage and Retrieval; D007802:Language; D016239:MEDLINE / Q000706:statistics & numerical data; D046650:Medical Subject Headings / Q000706:statistics & numerical data*; D011786:Quality Control; D035583:Rare Diseases; D009626:Terminology as Topic