科学医疗（英文）2025，Vol.4Issue(2)：110-143,34.DOI:10.1002/hcs2.70009
Rethinking Domain-Specific Pretraining by Supervised or Self-Supervised Learning for Chest Radiograph Classification:A Comparative Study Against ImageNet Counterparts in Cold-Start Active Learning
Rethinking Domain-Specific Pretraining by Supervised or Self-Supervised Learning for Chest Radiograph Classification:A Comparative Study Against ImageNet Counterparts in Cold-Start Active Learning
Han Yuan 1Mingcheng Zhu 1Rui Yang 2Han Liu 1Irene Li 3Chuan Hong4
作者信息
- 1. Duke-NUS Medical School,Centre for Quantitative Medicine,Singapore,Singapore
- 2. Department of Engineering Science,University of Oxford,Oxford,UK
- 3. Department of Computer Science,Vanderbilt University,Nashville,Tennessee,USA
- 4. Information Technology Center,University of Tokyo,Bunkyo-ku,Japan
- 折叠
摘要
关键词
chest radiograph analysis/cold-start active learning/COVID-19/psychiatric pneumonia/radiology foundation modelKey words
chest radiograph analysis/cold-start active learning/COVID-19/psychiatric pneumonia/radiology foundation model引用本文复制引用
Han Yuan,Mingcheng Zhu,Rui Yang,Han Liu,Irene Li,Chuan Hong..Rethinking Domain-Specific Pretraining by Supervised or Self-Supervised Learning for Chest Radiograph Classification:A Comparative Study Against ImageNet Counterparts in Cold-Start Active Learning[J].科学医疗（英文）,2025,4(2):110-143,34.
