Development of a CT-based comprehensive model with deep learning for differentiating pathological types of pulmonary ground-glass nodules
- DOI
- 10.3389/fmed.2026.1831127
- Published
- 2026-05-26
- Container
- Frontiers in Medicine
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fmed.2026.1831127,
title = {Development of a CT-based comprehensive model with deep learning for differentiating pathological types of pulmonary ground-glass nodules},
author = {Jian Zhang and Boheng Liu and Ji Li and Yang Liu and Jipeng Jiang},
year = {2026},
journal = {Frontiers in Medicine},
doi = {10.3389/fmed.2026.1831127},
url = {https://doi.org/10.3389/fmed.2026.1831127}
}RIS
TY - JOUR TI - Development of a CT-based comprehensive model with deep learning for differentiating pathological types of pulmonary ground-glass nodules AU - Jian Zhang AU - Boheng Liu AU - Ji Li AU - Yang Liu AU - Jipeng Jiang PY - 2026 JO - Frontiers in Medicine DO - 10.3389/fmed.2026.1831127 UR - https://doi.org/10.3389/fmed.2026.1831127 ER -
APA
Zhang, J., Liu, B., Li, J., Liu, Y., & Jiang, J. (2026). Development of a CT-based comprehensive model with deep learning for differentiating pathological types of pulmonary ground-glass nodules. Frontiers in Medicine. https://doi.org/10.3389/fmed.2026.1831127
Source records
- crossref · retrieved 2026-09-27T05:53:53.611Z