From black box to glass box: explainable artificial intelligence for acute kidney injury prediction-a scoping review and the GLASS-AKI translational framework proposal.

Lin WL, Fang SS, Chen SH

Open source

DOI
10.1007/s11255-026-05241-x
Published
2026 Jun 20
Container
International urology and nephrology
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1007/s11255-026-05241-x,
  title = {From black box to glass box: explainable artificial intelligence for acute kidney injury prediction-a scoping review and the GLASS-AKI translational framework proposal.},
  author = {Lin WL and Fang SS and Chen SH},
  year = {2026},
  journal = {International urology and nephrology},
  doi = {10.1007/s11255-026-05241-x},
  url = {https://doi.org/10.1007/s11255-026-05241-x}
}

RIS

TY  - JOUR
TI  - From black box to glass box: explainable artificial intelligence for acute kidney injury prediction-a scoping review and the GLASS-AKI translational framework proposal.
AU  - Lin WL
AU  - Fang SS
AU  - Chen SH
PY  - 2026
JO  - International urology and nephrology
DO  - 10.1007/s11255-026-05241-x
UR  - https://doi.org/10.1007/s11255-026-05241-x
ER  - 

APA

WL, L., SS, F., & SH, C. (2026). From black box to glass box: explainable artificial intelligence for acute kidney injury prediction-a scoping review and the GLASS-AKI translational framework proposal.. International urology and nephrology. https://doi.org/10.1007/s11255-026-05241-x

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