Feasibility of opportunistic screening for preserved ratio impaired spirometry using chest radiography-based deep learning models.
- DOI
- 10.1016/j.ejro.2026.100791
- Published
- 2026-07-06
- Container
- Eur J Radiol Open
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.ejro.2026.100791,
title = {Feasibility of opportunistic screening for preserved ratio impaired spirometry using chest radiography-based deep learning models.},
author = {Yoshida A and Kai C and Sato I and Futamura H and Oochi K and Kondo S and Kasai S.},
year = {2026},
journal = {Eur J Radiol Open},
doi = {10.1016/j.ejro.2026.100791},
url = {https://doi.org/10.1016/j.ejro.2026.100791}
}RIS
TY - JOUR TI - Feasibility of opportunistic screening for preserved ratio impaired spirometry using chest radiography-based deep learning models. AU - Yoshida A AU - Kai C AU - Sato I AU - Futamura H AU - Oochi K AU - Kondo S AU - Kasai S. PY - 2026 JO - Eur J Radiol Open DO - 10.1016/j.ejro.2026.100791 UR - https://doi.org/10.1016/j.ejro.2026.100791 ER -
APA
A, Y., C, K., I, S., H, F., K, O., S, K., & S., K. (2026). Feasibility of opportunistic screening for preserved ratio impaired spirometry using chest radiography-based deep learning models.. Eur J Radiol Open. https://doi.org/10.1016/j.ejro.2026.100791
Source records
- europe-pmc · retrieved 2026-09-26T07:08:19.425Z