FedEC-Dia: Explanation-Calibrated Federated Learning for Patient-Level Diabetes Digital Twin Risk Prediction Under Non-IID Healthcare Data.
- DOI
- 10.1109/jbhi.2026.3733118
- Published
- 2026 Sep 10
- Container
- IEEE journal of biomedical and health informatics
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/jbhi.2026.3733118,
title = {FedEC-Dia: Explanation-Calibrated Federated Learning for Patient-Level Diabetes Digital Twin Risk Prediction Under Non-IID Healthcare Data.},
author = {Tong Y and Hu K and Zhou Z and Yang T and Li X and Li J},
year = {2026},
journal = {IEEE journal of biomedical and health informatics},
doi = {10.1109/jbhi.2026.3733118},
url = {https://doi.org/10.1109/jbhi.2026.3733118}
}RIS
TY - JOUR TI - FedEC-Dia: Explanation-Calibrated Federated Learning for Patient-Level Diabetes Digital Twin Risk Prediction Under Non-IID Healthcare Data. AU - Tong Y AU - Hu K AU - Zhou Z AU - Yang T AU - Li X AU - Li J PY - 2026 JO - IEEE journal of biomedical and health informatics DO - 10.1109/jbhi.2026.3733118 UR - https://doi.org/10.1109/jbhi.2026.3733118 ER -
APA
Y, T., K, H., Z, Z., T, Y., X, L., & J, L. (2026). FedEC-Dia: Explanation-Calibrated Federated Learning for Patient-Level Diabetes Digital Twin Risk Prediction Under Non-IID Healthcare Data.. IEEE journal of biomedical and health informatics. https://doi.org/10.1109/jbhi.2026.3733118
Source records
- pubmed · retrieved 2026-09-25T11:34:38.494Z