Unveiling differential adverse event profiles in vaccines via LLM text embeddings and ontology semantic analysis
This study demonstrates the effectiveness of LLMs for automated AE extraction and analysis, and LLM text embeddings capture latent information about AEs, enabling more comprehensive knowledge discovery. Our findings suggest that LLMs demonstrate substantial potential for improving vaccine safety and public health research.
Authors
- Yongqun He (ORCID: https://orcid.org/0000-0001-9189-9661)
- Zhigang Wang (ORCID: https://orcid.org/0000-0003-1091-3893)
- Jie Zheng (ORCID: https://orcid.org/0000-0002-2999-0103)
- Xingxian Li
Institutions
- University of Michigan (US)
Publication Details
- Journal
- Journal of Biomedical Semantics
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1186/s13326-025-00331-8
- Citations
- 3
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- Peking Union Medical College
- National Institutes of Health