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Updated: Jun 25, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Query expansion with a medical ontology to improve a multimodal information retrieval system
M C Díaz-Galiano1, M T Martín-Valdivia, L A Ureña-López
1Departamento de Informática, Campus Las Lagunillas, s/n. University of Jaén, Jaén E-23071, Spain. mcdiaz@ujaen.es
Abstract:
Searching biomedical information in a large collection of medical data is a complex task. The use of tools and biomedical resources could ease the retrieval of the information desired. In this paper, we use the medical ontology MeSH to improve a Multimodal Information Retrieval System by expanding the user's query with medical terms. In order to accomplish our experiments, we have used the dataset provided by ImageCLEFmed task organizers for years 2005 and 2006. This dataset is composed of a multimodal collection (images and text) of clinical cases, a list of queries for each year, and a list of relevance judgments for each query to evaluate the results. The results from the experiments show that the use of a medical ontology to expand the queries greatly improves the results.
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