An AI-powered diagnostic system for grading and invasion of non-muscle-invasive bladder cancer via TURBT specimens: A multicenter study.

Zhang X, Wang H, Zhou H, Xiao D, Xiong H, Cheng J, He Y, Feng Q, Yang J

Open source

DOI
10.1016/j.isci.2026.116651
Published
2026 Jul 17
Container
iScience
Publisher
Not recorded
Open access
yes

Credibility signals

uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1016/j.isci.2026.116651,
  title = {An AI-powered diagnostic system for grading and invasion of non-muscle-invasive bladder cancer via TURBT specimens: A multicenter study.},
  author = {Zhang X and Wang H and Zhou H and Xiao D and Xiong H and Cheng J and He Y and Feng Q and Yang J},
  year = {2026},
  journal = {iScience},
  doi = {10.1016/j.isci.2026.116651},
  url = {https://doi.org/10.1016/j.isci.2026.116651}
}

RIS

TY  - JOUR
TI  - An AI-powered diagnostic system for grading and invasion of non-muscle-invasive bladder cancer via TURBT specimens: A multicenter study.
AU  - Zhang X
AU  - Wang H
AU  - Zhou H
AU  - Xiao D
AU  - Xiong H
AU  - Cheng J
AU  - He Y
AU  - Feng Q
AU  - Yang J
PY  - 2026
JO  - iScience
DO  - 10.1016/j.isci.2026.116651
UR  - https://doi.org/10.1016/j.isci.2026.116651
ER  - 

APA

X, Z., H, W., H, Z., D, X., H, X., J, C., Y, H., Q, F., & J, Y. (2026). An AI-powered diagnostic system for grading and invasion of non-muscle-invasive bladder cancer via TURBT specimens: A multicenter study.. iScience. https://doi.org/10.1016/j.isci.2026.116651

Source records