In-depth Analysis of Privacy Threats in Federated Learning for Medical Data.
- DOI
- 10.1109/jbhi.2026.3729148
- Published
- 2026-09-01
- Container
- IEEE J Biomed Health Inform
- Publisher
- Not recorded
- Open access
- no
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limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1109/jbhi.2026.3729148,
title = {In-depth Analysis of Privacy Threats in Federated Learning for Medical Data.},
author = {Das BC and Amini MH and Wu Y.},
year = {2026},
journal = {IEEE J Biomed Health Inform},
doi = {10.1109/jbhi.2026.3729148},
url = {https://doi.org/10.1109/jbhi.2026.3729148}
}RIS
TY - JOUR TI - In-depth Analysis of Privacy Threats in Federated Learning for Medical Data. AU - Das BC AU - Amini MH AU - Wu Y. PY - 2026 JO - IEEE J Biomed Health Inform DO - 10.1109/jbhi.2026.3729148 UR - https://doi.org/10.1109/jbhi.2026.3729148 ER -
APA
BC, D., MH, A., & Y., W. (2026). In-depth Analysis of Privacy Threats in Federated Learning for Medical Data.. IEEE J Biomed Health Inform. https://doi.org/10.1109/jbhi.2026.3729148
Source records
- europe-pmc · retrieved 2026-09-25T11:38:07.833Z