Predicting PD-L1+ CD8− status in NSCLC tissue from clinical indicators using machine learning
- DOI
- 10.1097/cm9.0000000000004257
- Published
- 2026-08-21
- Container
- Chinese Medical Journal
- Publisher
- Ovid Technologies (Wolters Kluwer Health)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1097/cm9.0000000000004257,
title = {Predicting PD-L1+ CD8− status in NSCLC tissue from clinical indicators using machine learning},
author = {Siwei Song and Yanling Ma and Zhe Jia and Guanghai Yang and Sufei Wang and Yuan Li and Yugang Hu and Hui Xia and Haoran Zheng and Yang Jin},
year = {2026},
journal = {Chinese Medical Journal},
doi = {10.1097/cm9.0000000000004257},
url = {https://doi.org/10.1097/cm9.0000000000004257}
}RIS
TY - JOUR TI - Predicting PD-L1+ CD8− status in NSCLC tissue from clinical indicators using machine learning AU - Siwei Song AU - Yanling Ma AU - Zhe Jia AU - Guanghai Yang AU - Sufei Wang AU - Yuan Li AU - Yugang Hu AU - Hui Xia AU - Haoran Zheng AU - Yang Jin PY - 2026 JO - Chinese Medical Journal DO - 10.1097/cm9.0000000000004257 UR - https://doi.org/10.1097/cm9.0000000000004257 ER -
APA
Song, S., Ma, Y., Jia, Z., Yang, G., Wang, S., Li, Y., Hu, Y., Xia, H., Zheng, H., & Jin, Y. (2026). Predicting PD-L1+ CD8− status in NSCLC tissue from clinical indicators using machine learning. Chinese Medical Journal. https://doi.org/10.1097/cm9.0000000000004257
Source records
- crossref · retrieved 2026-09-26T06:39:21.618Z