Wang, Yuqi, Wang, Zeqiang, Wang, Wei, Chen, Qi, Huang, Kaizhu, Nguyen, Anh 
ORCID: 0000-0002-1449-211X and De, Suparna
(2024)
Zero-Shot Medical Information Retrieval via Knowledge Graph Embedding.
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Abstract
In the era of the Internet of Things (IoT), the retrieval of relevant medical information has become essential for efficient clinical decision-making. This paper introduces MedFusionRank, a novel approach to zero-shot medical information retrieval (MIR) that combines the strengths of pre-trained language models and statistical methods while addressing their limitations. The proposed approach leverages a pre-trained BERT-style model to extract compact yet informative keywords. These keywords are then enriched with domain knowledge by linking them to conceptual entities within a medical knowledge graph. Experimental evaluations on medical datasets demonstrate MedFusionRank’s superior performance over existing methods, with promising results with a variety of evaluation metrics. MedFusionRank demonstrates efficacy in retrieving relevant information, even from short or single-term queries.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 26 Feb 2024 10:30 |
| Last Modified: | 26 Feb 2024 10:31 |
| DOI: | 10.1007/978-3-031-52216-1_3 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3178878 |
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