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Updated: May 24, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Performance evaluation of Unified Medical Language System®'s synonyms expansion to query PubMed
Nicolas Griffon1, Wiem Chebil, Laetitia Rollin
1CISMeF, Rouen University Hospital, Cour Leschevin, Porte 21, 3ème étage, 1 rue de Germont, 76031 Rouen Cedex, France.
Expanding PubMed searches with Unified Medical Language System (UMLS) synonyms improves retrieval of recent, non-indexed citations. This method enhances medical literature discovery by increasing recall and identifying current scientific advancements.
Area of Science:
- Medical Informatics
- Information Retrieval
Background:
- PubMed is a primary resource for accessing medical literature online.
- Enhancing PubMed's information retrieval is crucial for accessing non-indexed citations.
- The Unified Medical Language System (UMLS) organizes biomedical terms into concept unique identifiers.
Purpose of the Study:
- To evaluate a novel method for enhancing PubMed search performance.
- To improve the retrieval of non-indexed citations using query expansion with UMLS synonyms.
Main Methods:
- Query expansion using UMLS synonyms was implemented.
- The method was tested against current PubMed automatic term mapping.
- Citation relevance was assessed by four expert evaluators.
Main Results:
- UMLS-enhanced queries retrieved new citations for 45.5% of cases, increasing recall.
- A 23.7% mean increase in retrieved non-indexed citations was observed.
- 82% of these newly retrieved citations were published within the last four months.
- Overall mean precision was 48.4%, with significant inter-rater variability (kappa = 0.34).
Conclusions:
- The study underscores the need for tailored search tools for diverse user needs and applications.
- The proposed UMLS synonym expansion strategy shows potential for discovering recent scientific advancements.
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