Assessing the enrichment of dietary supplement coverage in the unified medical language system

Jake Vasilakes, Anusha Bompelli, Jeffrey R. Bishop, Terrence J. Adam, Olivier Bodenreider, Rui Zhang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Objective: We sought to assess the need for additional coverage of dietary supplements (DS) in the Unified Medical Language System (UMLS) by investigating (1) the overlap between the integrated DIetary Supplements Knowledge base (iDISK) DS ingredient terminology and the UMLS and (2) the coverage of iDISK and the UMLS over DS mentions in the biomedical literature. Materials and Methods: We estimated the overlap between iDISK and the UMLS by mapping iDISK to the UMLS using exact and normalized strings. The coverage of iDISK and the UMLS over DS mentions in the biomedical literature was evaluated via a DS named-entity recognition (NER) task within PubMed abstracts. Results: The coverage analysis revealed that only 30% of iDISK terms can be matched to the UMLS, although these cover over 99% of iDISK concepts. A manual review revealed that a majority of the unmatched terms represented new synonyms, rather than lexical variants. For NER, iDISK nearly doubles the precision and achieves a higher F1 score than the UMLS, while maintaining a competitive recall. Discussion: While iDISK has significant concept overlap with the UMLS, it contains many novel synonyms. Furthermore, almost 3000 of these overlapping UMLS concepts are missing a DS designation, which could be provided by iDISK. The NER experiments show that the specialization of iDISK is useful for identifying DS mentions. Conclusions: Our results show that the DS representation in the UMLS could be enriched by adding DS designations to many concepts and by adding new synonyms.

Original languageEnglish (US)
Pages (from-to)1547-1555
Number of pages9
JournalJournal of the American Medical Informatics Association
Issue number10
StatePublished - Oct 1 2020

Bibliographical note

Funding Information:
This work was supported by the National Institutes of Health?s National Center for Complementary and Integrative Health and the Office of Dietary Supplements grant number R01AT009457 (to RZ), the National Center for Advancing Translational Sciences grant number UL1TR002494 (to Bruce Blazer), and the Intramural Research Program of the National Library of Medicine. The content is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health.

Publisher Copyright:
© The Author(s) 2020.


  • Dietary supplements
  • Named entity recognition
  • Natural language processing
  • Terminology
  • Unified medical language system


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