AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.
- DOI
- 10.1007/s00464-025-12534-2
- Published
- 2026-01-14
- Container
- Surg Endosc
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1007/s00464-025-12534-2,
title = {AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.},
author = {Yoon D and Chang SH and Paik WH and Kim CH and Kim BS and Kim YG and Chung H and Ryu JK and Lee SH and Cho IR and Choi SJ and Kim JS and Kim S and Choi JH.},
year = {2026},
journal = {Surg Endosc},
doi = {10.1007/s00464-025-12534-2},
url = {https://doi.org/10.1007/s00464-025-12534-2}
}RIS
TY - JOUR TI - AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging. AU - Yoon D AU - Chang SH AU - Paik WH AU - Kim CH AU - Kim BS AU - Kim YG AU - Chung H AU - Ryu JK AU - Lee SH AU - Cho IR AU - Choi SJ AU - Kim JS AU - Kim S AU - Choi JH. PY - 2026 JO - Surg Endosc DO - 10.1007/s00464-025-12534-2 UR - https://doi.org/10.1007/s00464-025-12534-2 ER -
APA
D, Y., SH, C., WH, P., CH, K., BS, K., YG, K., H, C., JK, R., SH, L., IR, C., SJ, C., JS, K., S, K., & JH., C. (2026). AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.. Surg Endosc. https://doi.org/10.1007/s00464-025-12534-2
Source records
- europe-pmc · retrieved 2026-09-27T11:55:42.089Z