Federated learning for privacy-preserving ophthalmic artificial intelligence: clinical applications and translational challenges.
- DOI
- 10.3389/fmed.2026.1904004
- Published
- 2026
- Container
- Frontiers in medicine
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
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Cite this work
BibTeX
@article{allodium:10.3389/fmed.2026.1904004,
title = {Federated learning for privacy-preserving ophthalmic artificial intelligence: clinical applications and translational challenges.},
author = {Wei Y and Zhao K and Grzybowski A and Jin K},
year = {2026},
journal = {Frontiers in medicine},
doi = {10.3389/fmed.2026.1904004},
url = {https://doi.org/10.3389/fmed.2026.1904004}
}RIS
TY - JOUR TI - Federated learning for privacy-preserving ophthalmic artificial intelligence: clinical applications and translational challenges. AU - Wei Y AU - Zhao K AU - Grzybowski A AU - Jin K PY - 2026 JO - Frontiers in medicine DO - 10.3389/fmed.2026.1904004 UR - https://doi.org/10.3389/fmed.2026.1904004 ER -
APA
Y, W., K, Z., A, G., & K, J. (2026). Federated learning for privacy-preserving ophthalmic artificial intelligence: clinical applications and translational challenges.. Frontiers in medicine. https://doi.org/10.3389/fmed.2026.1904004