Empowering PET imaging reporting with retrieval-augmented large language models and reading reports database: a pilot single center study
The integration of RAG LLM with a large database of PET imaging reports suggests the potential to support clinical practice of nuclear medicine imaging reading by various tasks of AI including finding similar cases and deriving potential diagnoses from them. This study underscores the potential of advanced AI tools in transforming medical imaging reporting practices.
Authors
- Dongjoo Lee (ORCID: https://orcid.org/0000-0001-9381-0376)
- Minseok Suh (ORCID: https://orcid.org/0000-0002-6932-8552)
- Hongyoon Choi (ORCID: https://orcid.org/0000-0002-8895-2449)
- Yeon-koo Kang
Institutions
- Seoul National University (KR)
- Seoul National University Hospital (KR)
- KRI (JP)
- National University College (PR)
Publication Details
- Journal
- European Journal of Nuclear Medicine and Molecular Imaging
- Published
- 2025-01-22
- DOI
- https://doi.org/10.1007/s00259-025-07101-9
- Citations
- 10
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 6.54
Funders
- Seoul National University Hospital