Computed tomography-based radiomic features combined with clinical parameters for predicting post-infectious bronchiolitis obliterans in children with adenovirus pneumonia: a retrospective study
Combining CT-based radiomic features with clinical parameters can offer an effective noninvasive model to predict BO in children with adenovirus pneumonia.
Authors
- Xiaoyin Tian
- Haoru Wang (ORCID: https://orcid.org/0000-0003-2497-0872)
- Fang Wang (ORCID: https://orcid.org/0000-0002-9541-7743)
- Xin Chen (ORCID: https://orcid.org/0000-0003-3024-9053)
- Man Li (ORCID: https://orcid.org/0000-0002-3839-0281)
- Li Zhang (ORCID: https://orcid.org/0000-0001-7700-0357)
- Yang Li (ORCID: https://orcid.org/0009-0005-9275-8648)
- Zhengxiu Luo (ORCID: https://orcid.org/0000-0003-2569-753X)
- Ling He (ORCID: https://orcid.org/0000-0003-4389-7973)
- Yinglan Zheng
- Guangli Zhang (ORCID: https://orcid.org/0000-0002-7288-3637)
Institutions
- United Imaging Healthcare (China) (CN)
- Children's Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- PeerJ
- Published
- 2025-03-31
- DOI
- https://doi.org/10.7717/peerj.19145
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36