Searching for rare diseases in PubMed: a blind comparison of Orphanet expert query and query based on terminological knowledge

Autor: Matthieu Schuers, Ferdinand Dhombres, Laetitia Rollin, Stéfan J. Darmoni, Nicolas Griffon, Tayeb Merabti, Gaétan Kerdelhué
Přispěvatelé: Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Université Paris 13 (UP13)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de Médecine Générale [Rouen] (DMG), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de santé au travail et pathologie professionnelle [Rouen], CHU Rouen, Normandie Université (NU), This work was performed on authors institutionnal own fundings., BMC, BMC, Service de Médecine Fœtale [CHU Trousseau], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH)
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, 2015, 16 (1), pp.101. ⟨10.1186/s12911-016-0333-0⟩
BMC Medical Informatics and Decision Making, BioMed Central, 2015, 16 (1), pp.101. ⟨10.1186/s12911-016-0333-0⟩
ISSN: 1472-6947
Popis: Background Despite international initiatives like Orphanet, it remains difficult to find up-to-date information about rare diseases. The aim of this study is to propose an exhaustive set of queries for PubMed based on terminological knowledge and to evaluate it versus the queries based on expertise provided by the most frequently used resource in Europe: Orphanet. Methods Four rare disease terminologies (MeSH, OMIM, HPO and HRDO) were manually mapped to each other permitting the automatic creation of expended terminological queries for rare diseases. For 30 rare diseases, 30 citations retrieved by Orphanet expert query and/or query based on terminological knowledge were assessed for relevance by two independent reviewers unaware of the query’s origin. An adjudication procedure was used to resolve any discrepancy. Precision, relative recall and F-measure were all computed. Results For each Orphanet rare disease (n = 8982), there was a corresponding terminological query, in contrast with only 2284 queries provided by Orphanet. Only 553 citations were evaluated due to queries with 0 or only a few hits. There were no significant differences between the Orpha query and terminological query in terms of precision, respectively 0.61 vs 0.52 (p = 0.13). Nevertheless, terminological queries retrieved more citations more often than Orpha queries (0.57 vs. 0.33; p = 0.01). Interestingly, Orpha queries seemed to retrieve older citations than terminological queries (p
Databáze: OpenAIRE
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