Evaluation of radiology residents’ reporting skills using large language models: an observational study
LLMs can effectively provide feedback on commonly corrected areas in radiology reports, enabling residents to objectively identify and improve their weaknesses and monitor their progress. Additionally, LLMs may help reduce the workload of radiologists' mentors.
Authors
- Taro Shimono (ORCID: https://orcid.org/0000-0001-5847-6587)
- Yukio Miki (ORCID: https://orcid.org/0000-0003-0621-0044)
- Tatsushi Oura (ORCID: https://orcid.org/0000-0002-0930-1032)
- Yasuhito Mitsuyama (ORCID: https://orcid.org/0000-0001-7979-2300)
- Akiko Omori (ORCID: https://orcid.org/0009-0002-9279-6917)
- Daisuke Horiuchi (ORCID: https://orcid.org/0000-0002-8929-8098)
- Natsuko Atsukawa (ORCID: https://orcid.org/0009-0001-7170-1029)
- Hirotaka Takita (ORCID: https://orcid.org/0000-0003-2860-4503)
- Hiroyuki Tatekawa (ORCID: https://orcid.org/0000-0002-8050-4895)
- Shu Matsushita (ORCID: https://orcid.org/0000-0003-1132-9736)
- Daiju Ueda (ORCID: https://orcid.org/0000-0002-3878-3616)
Institutions
- Osaka City University Hospital (JP)
- Osaka Metropolitan University (JP)
- Tokyo Metropolitan University (JP)
Publication Details
- Journal
- Japanese Journal of Radiology
- Published
- 2025-03-08
- DOI
- https://doi.org/10.1007/s11604-025-01764-y
- Citations
- 10
- Primary Topic
- Radiology practices and education
- Type
- article
- Field-Weighted Citation Impact
- 13.60
Funders
- Guerbet