Prediction of active drug-resistant pulmonary tuberculosis based on CT radiomics: construction and validation of independent models and combined models for residual pulmonary parenchyma
The newly defined and developed RPP model and the combined model demonstrated robust performance in identifying DR-TB, highlighting the potential of CT-based radiomic models as effective non-invasive tools for DR-TB prediction.
Authors
- Yuting Jiang (ORCID: https://orcid.org/0000-0001-7404-5250)
- Mingke Liu
- Huang Mingxin (ORCID: https://orcid.org/0000-0002-3351-7001)
- Liangbo Hu
- X. Chen
- Yongxia Zhou (ORCID: https://orcid.org/0000-0002-4931-2318)
- Fangli Wei (ORCID: https://orcid.org/0000-0002-9090-4753)
- Fang Wang (ORCID: https://orcid.org/0000-0002-3044-0571)
- Shaoping Nie (ORCID: https://orcid.org/0000-0003-0664-5857)
- Jing Ding (ORCID: https://orcid.org/0009-0006-8052-7129)
Institutions
- United Imaging Healthcare (China) (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-03-31
- DOI
- https://doi.org/10.3389/fmed.2025.1508736
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36