Improving breast ultrasonography education: the impact of AI-based decision support on the performance of non-specialist medical professionals
The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.
Authors
- Hye Sun Lee (ORCID: https://orcid.org/0000-0001-6328-6948)
- Jaeil Kim (ORCID: https://orcid.org/0000-0002-9799-1773)
- Jung Hyun Yoon (ORCID: https://orcid.org/0000-0002-2100-3513)
- Sangwon Lee (ORCID: https://orcid.org/0000-0001-6960-5487)
- Eun‐Ju Lee (ORCID: https://orcid.org/0000-0003-4612-0625)
- Won Hwa Kim (ORCID: https://orcid.org/0000-0001-7137-9968)
Institutions
- Yonsei University (KR)
- Severance Hospital (KR)
- Kyungpook National University Hospital (KR)
- Kyungpook National University (KR)
- Skyworks Solutions (United States) (US)
Publication Details
- Journal
- ULTRASONOGRAPHY
- Published
- 2024-12-11
- DOI
- https://doi.org/10.14366/usg.24171
- Citations
- 4
- Primary Topic
- Radiology practices and education
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Korea Medical Device Development Fund
- Ministry of Trade, Industry and Energy
- Ministry of Food and Drug Safety
- Ministry of Science and ICT, South Korea