A retrieval-augmented knowledge mining method with deep thinking LLMs for biomedical research and clinical support
The IP-RAR helps doctors efficiently integrate treatment evidence to inform the development of personalized medication plans and enables researchers to analyze advancements and research gaps, accelerating the hypothesis generation phase of scientific discovery and decision-making.
Authors
- Yixue Li (ORCID: https://orcid.org/0000-0002-1198-7176)
- Yichun Feng (ORCID: https://orcid.org/0009-0007-4511-4713)
- Lu Zhou
- Ruikun He (ORCID: https://orcid.org/0000-0002-2292-8884)
- Jiawei Wang (ORCID: https://orcid.org/0009-0005-0575-2695)
Institutions
- University of Science and Technology of China (CN)
- Hefei University of Technology (CN)
- Shanghai Jiao Tong University (CN)
- Guangzhou Experimental Station (CN)
- Shanghai Institute of Nutrition and Health (CN)
- Guangzhou Regenerative Medicine and Health Guangdong Laboratory (CN)
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality (CN)
- ZheJiang Academy of Agricultural Sciences (CN)
- University of Chinese Academy of Sciences (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- GigaScience
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1093/gigascience/giaf109
- Citations
- 5
- Primary Topic
- Data Mining Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 16.23