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Updated: Jun 4, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
A Comprehensive Analysis of Five Million UMLS Metathesaurus Terms Using Eighteen Million MEDLINE Citations
Rong Xu1, Mark A Musen, Nigam H Shah
1Center for Biomedical Informatics Research, Stanford University School of Medicine Stanford, CA 94305, USA.
Abstract:
The Unified Medical Language System (UMLS) Metathesaurus is widely used for biomedical natural language processing (NLP) tasks. In this study, we systematically analyzed UMLS Metathesaurus terms by analyzing their occurrences in over 18 million MEDLINE abstracts. Our goals were: 1. analyze the frequency and syntactic distribution of Metathesaurus terms in MEDLINE; 2. create a filtered UMLS Metathesaurus based on the MEDLINE analysis; 3. augment the UMLS Metathesaurus where each term is associated with metadata on its MEDLINE frequency and syntactic distribution statistics. After MEDLINE frequency-based filtering, the augmented UMLS Metathesaurus contains 518,835 terms and is roughly 13% of its original size. We have shown that the syntactic and frequency information is useful to identify errors in the Metathesaurus. This filtered and augmented UMLS Metathesaurus can potentially be used to improve efficiency and precision of UMLS-based information retrieval and NLP tasks.
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