Completing missing MeSH code mappings in UMLS through alternative expert-curated sources

Abstract

The increasing availability of biological, clinical and literary sources enables the study of diseases from a more comprehensive approach. However, the interoperability of these sources, particularly of the codes used to identify diseases, poses a major challenge. Because of its role as a hub of multiple medical vocabularies, the Unified Medical Language System (UMLS) has become one of the most widely used resources for mapping diseases from different classification systems. The coverage of these mappings, nevertheless, is still insufficient, so researchers must resort to other methods to fill these gaps. In this article we analyze the limitations in UMLS mappings for the MeSH, ICD-10 and SNOMED CT vocabularies and propose the exploitation of alternative expert-curated sources to complete it. As a result, we demonstrate that this approach allows resolving more than 50% of the missing mappings for these vocabularies. All the findings are shared for validation and reuse.