Mapping Drug Terms via Integration of a Retrieval-Augmented Generation Algorithm with a Large Language Model
Integrating an RAG and an LLM outperformed conventional string comparison and embedding vector similarity techniques, offering a more refined approach to global drug information mapping.
Authors
- Eizen Kimura (ORCID: https://orcid.org/0000-0002-0690-8568)
- Yukinobu Kawakami
- Shingo Inoue
- Ai Okajima
Institutions
- Tokyo University of Information Sciences (JP)
- Ehime Medical Center (JP)
- Ehime University (JP)
Publication Details
- Journal
- Healthcare Informatics Research
- Published
- 2024-10-31
- DOI
- https://doi.org/10.4258/hir.2024.30.4.355
- Citations
- 5
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 1.17
Funders
- Ministry of Education, Culture, Sports, Science and Technology