Towards the automated generation of expert profiles for rare diseases through bibliometric analysis.
For patients suffering from rare diseases it is often hard to find an expert clinician. Existing registries rely on manual registration procedures and cannot easily be kept up to date. A prototype data collection system for discovering experts on rare diseases using MEDLINE has been successfully deployed. Initial manual analyses demonstrate proof of concept and deliver promising results. Examining the associations between authors, diseases and MeSH-Terms is expected to open up a variety of possibilities beyond expert discovery.
Division of Neurophysiology, Ulm University.
Andreas
A
Pflugrad
Division of Neurophysiology, Ulm University.
Karin
K
Jurkat-Rott
Division of Neurophysiology, Ulm University.
Frank
F
Lehmann-Horn
Centre of Rare Diseases Ulm in the Centre of Excellence for Rare Diseases, Baden-Württemberg.
Jochen
J
Bernauer
D001319:Authorship; D015706:Bibliometrics; D002983:Clinical Competence / Q000706:statistics & numerical data*; D057225:Data Mining / Q000379:methods*; D005104:Expert Testimony; D006801:Humans; D016239:MEDLINE / Q000706:statistics & numerical data*; D046650:Medical Subject Headings; D009323:Natural Language Processing; D035583:Rare Diseases / Q000145:classification*; D012017:Referral and Consultation / Q000145:classification*; D018875:Vocabulary, Controlled