Stacked CT radiomics, deep learning and clinical feature models for differentiating benign and malignant solitary pulmonary nodules
- DOI
- 10.1038/s41598-026-49720-8
- Published
- 2026-04-28
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-49720-8,
title = {Stacked CT radiomics, deep learning and clinical feature models for differentiating benign and malignant solitary pulmonary nodules},
author = {Jie Zong and Biyun Jiang and Haiyan Li and Zhiling Li},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-49720-8},
url = {https://doi.org/10.1038/s41598-026-49720-8}
}RIS
TY - JOUR TI - Stacked CT radiomics, deep learning and clinical feature models for differentiating benign and malignant solitary pulmonary nodules AU - Jie Zong AU - Biyun Jiang AU - Haiyan Li AU - Zhiling Li PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-49720-8 UR - https://doi.org/10.1038/s41598-026-49720-8 ER -
APA
Zong, J., Jiang, B., Li, H., & Li, Z. (2026). Stacked CT radiomics, deep learning and clinical feature models for differentiating benign and malignant solitary pulmonary nodules. Scientific Reports. https://doi.org/10.1038/s41598-026-49720-8
Source records
- crossref · retrieved 2026-11-04T18:34:28.961Z