The impact of maximum cross-sectional area of lesion on predicting the early therapeutic response of multidrug-resistant tuberculosis
The integration of maximum lesion cross-sectional area during treatment can improve the prediction of early treatment response in MDR-TB. When applied in a clinical setting, the random forest model is more suitable for guiding appropriate treatment plans quickly.
Authors
- Yu Pang (ORCID: https://orcid.org/0000-0001-6803-9807)
- Zi-Long Yang
- Shanshan Li (ORCID: https://orcid.org/0000-0003-4475-4536)
- Liang Li (ORCID: https://orcid.org/0000-0001-8701-1113)
- Fuzhen Zhang (ORCID: https://orcid.org/0000-0002-5056-3886)
- Yu Zhang (ORCID: https://orcid.org/0000-0002-5430-6772)
- Ruichao Liu (ORCID: https://orcid.org/0009-0003-4214-5988)
Institutions
- Beijing Chest Hospital (CN)
- Indiana University Bloomington (US)
- Guangzhou Chest Hospital (CN)
Publication Details
- Journal
- Journal of Infection and Public Health
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1016/j.jiph.2024.102628
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.40