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Updated: May 15, 2026
05:47
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Semantics-driven modelling of user preferences for information retrieval in the biomedical domain
Anatoly Gladun1, Julia Rogushina, Rafael Valencia-García
1International Research and Training Centre of Information Technologies and Systems, National Academy of Sciences and Ministry of Education of Ukraine, Ukraine.
Informatics for Health & Social Care
|January 18, 2013
Summary
This study introduces an ontology-based system to organize and retrieve biomedical data. By using domain ontologies, it enhances information retrieval for researchers.
Area of Science:
- Biomedical Informatics
- Semantic Web Technologies
- Knowledge Representation
Background:
- Vast amounts of biomedical and genomic data are publicly available online.
- Data is fragmented across diverse, unorganized biological information sources.
- Semantic technologies offer solutions for data organization, manipulation, and visualization.
Purpose of the Study:
- To develop an ontology-based information retrieval system for the biomedical domain.
- To improve the organization and accessibility of distributed biomedical data.
- To leverage semantic technologies for enhanced data management and knowledge discovery.
Main Methods:
- Utilized domain ontologies for knowledge representation.
- Developed interoperable algorithms for information retrieval.
- Created lightweight ontologies representing user preferences within specific domains.
- Normalized ontologies to ensure consistency and facilitate data integration.
Main Results:
- Demonstrated the effectiveness of the ontology-based system in improving information retrieval.
- Showcased the application of domain and ontological information to refine search processes.
- Validated the system through experimental evaluations described in the paper.
Conclusions:
- Ontology-based approaches significantly enhance biomedical information retrieval.
- The developed system provides a structured method for managing and accessing complex biological data.
- This work contributes to the advancement of semantic technologies in bioinformatics and data science.
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