Leveraging terminological resources for mapping between rare disease information sources.
BACKGROUND
Rare disease information sources are incompletely and inconsistently cross-referenced to one another, making it difficult for information seekers to navigate across them. The development of such cross-references established manually by experts is generally labor intensive and costly.


OBJECTIVE
To develop an automatic mapping between two of the major rare diseases information sources, GARD and Orphanet, by leveraging terminological resources, especially the UMLS.


METHODS
We map the rare disease terms from Orphanet and ORDR to the UMLS. We use the UMLS as a pivot to bridge between the rare disease terminologies. We compare our results to a mapping obtained through manually established cross-references to OMIM.


RESULTS
Our mapping has a precision of 94%, a recall of 63% and an F1-score of 76%. Our automatic mapping should help facilitate the development of more complete and consistent cross-references between GARD and Orphanet, and is applicable to other rare disease information sources as well.
U.S. National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
Bastien
B
Rance
Michelle
M
Snyder
Janine
J
Lewis
Olivier
O
Bodenreider
D001185:Artificial Intelligence; D003628:Database Management Systems; D016208:Databases, Factual; D016247:Information Storage and Retrieval / Q000379:methods*; D008498:Medical Record Linkage / Q000379:methods*; D009323:Natural Language Processing; D035583:Rare Diseases / Q000145:classification*; D012660:Semantics; D017432:Unified Medical Language System; D014584:User-Computer Interface