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 Apr 28
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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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 = {Zong J and Jiang B and Li H and Li Z},
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 - Zong J AU - Jiang B AU - Li H AU - Li Z PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-49720-8 UR - https://doi.org/10.1038/s41598-026-49720-8 ER -
APA
J, Z., B, J., H, L., & Z, L. (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
- pubmed · retrieved 2026-09-25T14:59:52.858Z