A CT-Based Lung Radiomics Nomogram for Classifying the Severity of Chronic Obstructive Pulmonary Disease
The present work constructed and verified the novel, diagnostic radiomics nomogram for identifying the severity of COPD, showing the added value of chest CT to evaluate not only the pulmonary structure but also the lung function status.
Authors
- Shiyuan Liu (ORCID: https://orcid.org/0000-0003-3420-0310)
- Li Fan (ORCID: https://orcid.org/0000-0003-4722-3933)
- Xiuxiu Zhou (ORCID: https://orcid.org/0000-0003-2405-0566)
- Taohu Zhou (ORCID: https://orcid.org/0000-0001-6208-2249)
- Xiaoqing Lin (ORCID: https://orcid.org/0000-0002-1690-136X)
- Zhaobin Li (ORCID: https://orcid.org/0000-0003-2224-7074)
- Wenjun Huang (ORCID: https://orcid.org/0000-0002-2765-3381)
- Wenting Tu (ORCID: https://orcid.org/0000-0003-1010-7189)
- Jie Li (ORCID: https://orcid.org/0000-0001-7163-3778)
- Yi Xia (ORCID: https://orcid.org/0009-0009-4746-5845)
- Yun Wang (ORCID: https://orcid.org/0000-0001-8914-9861)
- Xiang Wang (ORCID: https://orcid.org/0000-0002-0105-9755)
- Peng Dong (ORCID: https://orcid.org/0009-0002-5686-0758)
- Yu Guan (ORCID: https://orcid.org/0000-0001-9416-058X)
- Jiong Ni
- Xin’ang Jiang
Institutions
- Tongji University (CN)
- University of Shanghai for Science and Technology (CN)
- Shanghai Jiao Tong University (CN)
- Deyang Stomatological Hospital (CN)
- Shanghai Sixth People's Hospital (CN)
- Xian Yang Central Hospital (CN)
- Tongji Hospital (CN)
Publication Details
- Journal
- International Journal of COPD
- Published
- 2024-12-01
- DOI
- https://doi.org/10.2147/copd.s483007
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Health Commission of the People's Republic of China
- National Key Research and Development Program of China