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. OBJECTIVES: 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.
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. OBJECTIVES: 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.