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
- Container
- IEEE Journal of Biomedical and Health Informatics
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- 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 = {Yao Tong and Kongfa Hu and Zuojian Zhou and Tao Yang and Xin Li and Jiaxin Li},
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 - Yao Tong AU - Kongfa Hu AU - Zuojian Zhou AU - Tao Yang AU - Xin Li AU - Jiaxin Li 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
Tong, Y., Hu, K., Zhou, Z., Yang, T., Li, X., & Li, J. (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
- crossref · retrieved 2026-11-10T12:47:27.031Z