Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model
The AdaBoost-based prediction model, developed using CT radiomic features, effectively differentiates large opacities of stage III occupational pneumoconiosis from peripheral lung cancer.
Authors
- Wei Wang (ORCID: https://orcid.org/0000-0002-8984-6795)
- Li Wang (ORCID: https://orcid.org/0000-0002-0081-5491)
- Qian Li (ORCID: https://orcid.org/0000-0002-9530-4925)
- Qianqian Liu (ORCID: https://orcid.org/0000-0003-3724-4394)
- Xiaolong Li (ORCID: https://orcid.org/0000-0002-3909-1953)
- Xiaobing Li (ORCID: https://orcid.org/0000-0001-6417-6054)
- Li Zhang (ORCID: https://orcid.org/0000-0003-0665-8885)
- Wutao Xie
- Yongsheng Liu (ORCID: https://orcid.org/0000-0002-0956-8693)
Institutions
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Public Health Medical Center (CN)
- Chongqing Medical and Pharmaceutical College (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-12-03
- DOI
- https://doi.org/10.3389/fmed.2025.1675840
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chongqing Municipal Health Commission
- Chongqing Medical University
- Natural Science Foundation of Chongqing
- Chongqing Municipal Education Commission
- Centre Scientifique et Technique du Bâtiment