Deep Learning Approaches to Address the Shortage of Observers
Our results suggest that replacing human observers with AI has a minimal impact and may help alleviate observer shortages. The main limitation is the inability to modify evaluation criteria or stages with the trained models.
Authors
- Tomoya Masumoto
- K. Kitajima
- Tetsuya Ijichi (ORCID: https://orcid.org/0009-0004-2627-682X)
- Tadamitsu Ideguchi
- Asami Obata
- Yuna Kawahara
- Nariaki Tabata (ORCID: https://orcid.org/0009-0002-2280-9778)
- Lisa Sonoda
- Shinichi Katou
- Toshirou Inoue
- Masaya Tominaga
- Shuto Okaba
Institutions
- Kyushu University (JP)
- Fukuoka University (JP)
- Department of Medical Sciences (BY)
Publication Details
- Journal
- Japanese Journal of Radiological Technology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.6009/jjrt.25-1554
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00