Identification of PD-L1 Expression in Resectable NSCLC using Interpretable Machine Learning Model Based on Spectral CT
The XGBoost model, integrating spectral CT quantitative parameters and imaging features, demonstrated considerable potential in predicting PDL1 expression.
Authors
- Xiaodan Zhao (ORCID: https://orcid.org/0000-0003-1469-8027)
- Hongzheng Song (ORCID: https://orcid.org/0009-0007-0972-1073)
- Henan Lou
- Shiyu Cui (ORCID: https://orcid.org/0000-0003-1305-2259)
- Shaoke Li
- Yinying Dong (ORCID: https://orcid.org/0009-0007-0660-5093)
- Shunli Liu (ORCID: https://orcid.org/0000-0001-7571-9675)
Institutions
- Qingdao University (CN)
- Affiliated Hospital of Qingdao University (CN)
- Qingdao Municipal Hospital (CN)
Publication Details
- Journal
- Current Medical Imaging Formerly Current Medical Imaging Reviews
- Published
- 2025-10-15
- DOI
- https://doi.org/10.2174/0115734056404160250925115913
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00