Variation-Aware Federated Learning With Multi-Source Decentralized Medical Image Data

ImageNet Large Scale Visual Recognition Challenge

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Unpaired image-to-image translation using cycle-consistent adversarial networks

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Cancer statistics, 2020

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Communication-Efficient Learning of Deep Networks from Decentralized Data

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Learning Deep Features for Discriminative Localization

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Improved training of Wasserstein GANs

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Federated Machine Learning: Concept and Applications

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Membership Inference Attacks Against Machine Learning Models

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The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

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Enhancing Medical Data Analysis with Federated Learning in the Internet of Medical Things

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Mixed Federated Learning Approach for Multiclass Image Segmentation

Praneeth, E., Reddy, Y., Abhiram, D., Gopalachari, M. V., Kiranmaie, P., & Rakesh, S. (2024) · Recent Advances in Sustainable Engineering and Future Technologies (RASEFT) · doi:10.1109/raseft61414.2024.00029 · Cited by 2

Federated Learning for Secure and Privacy‐Aware Internet of Medical Things: Taxonomy, Emerging Applications, Open Challenges, and Future Directions

Wani, R. U. Z., & Can, Ö. (2025) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.70432 · Cited by 3

Dual-driven synergy of blockchain and federated learning for trustworthy medical data sharing in internet of medical things

Gan, C., Tan, X., Zhu, Q., Saini, A., Jain, D. K., & Diro, A. A. (2025) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2025.104348 · Cited by 2

Secure Federated Learning

Jin, Y., Zhu, H., Xu, J., & Chen, Y. (2022) · Machine learning · doi:10.1007/978-981-19-7083-2_4 · Cited by 2

Federated learning for prostate cancer detection in biparametric MRI: optimization of rounds, epochs, and aggregation strategy

Moradi, A., Zerka, F., Bosma, J. S., Yakar, D., Geerdink, J., Huisman, H. J., Bathen, T. F., & Elschot, M. (2024) · SPIE Medical Imaging: Computer-Aided Diagnosis · doi:10.1117/12.2688568 · Cited by 2

Heterogeneous Personalized Privacy Protection for Internet of Medical Things: A Blockchain-based Federated Learning Approach

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Robust Federated Learning Based on Chained Self-Paced Learning

Jia, Y., Li, W., Yan, M., & Yan, B. (2023) · International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI) · doi:10.1109/cei60616.2023.10527834 · Cited by 2

A Comprehensive Survey on Federated Learning and its Applications in Health Care

Pacheco, S. A. B. (2024) · IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) · doi:10.1109/iicaiet62352.2024.10730687 · Cited by 2

A Differential Privacy Federated Learning Approach for Diabetic Retinopathy Detection

Li, Y., Zhang, Y., Liu, G., & Lu, M. (2024) · Lecture notes in computer science · doi:10.1007/978-981-96-0840-9_13 · Cited by 3

Optimizing Federated Learning Configurations for MRI Prostate Segmentation and Cancer Detection: A Simulation Study

Moradi, A., Zerka, F., Bosma, J. S., Sunoqrot, M. R. S., Abrahamsen, B. S., Yakar, D., Geerdink, J., Huisman, H. J., Bathen, T. F., & Elschot, M. (2025) · Radiology Artificial Intelligence · doi:10.1148/ryai.240485 · Cited by 3

Personalized federated adaptive regularization for heterogeneous medical image classification: COVID-19 CT results

Liu, Y., Qu, Z., Wang, S., Sheng, T., Yu, X., & Wang, J. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385702 · Cited by 2

Collaborative Multi-Institutional Prostate Lesion Segmentation from MR images Using Deep Federated Learning Framework

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A Federated Learning-Based Precision Prediction Model for External Elastic Membrane and Lumen Boundary Segmentation in Intravascular Ultrasound Images

Hsiao, C., Peng, T.-Y., Huang, W., Teng, H.-I., Lu, T., Lin, F. Y., & Huang, Y. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-99584-3_33 · Cited by 2

Multi-center Federated Learning with Model Decoupling

Wang, B., Lu, T., Guo, W., Chang, S., Liu, G., Huang, Q., & Yang, P. (2022) · International Conference on Computer Science and Management Technology (ICCSMT) · doi:10.1109/iccsmt58129.2022.00101 · Cited by 1

Distributed swarm learning for communication-efficient capsule endoscopy classification on solving Non-i.i.d data

Huang, J., Wu, W., Hu, D., Sun, X., Wu, W., & Xu, J. (2025) · Alexandria Engineering Journal · doi:10.1016/j.aej.2025.05.008 · Cited by 1

Federated learning framework for predicting multi-drug resistant tuberculosis across regional databases

Bhute, H. A., Bhute, A. N., Waghulde, K. B., Vasgi, B. P., Sonar, R., & Deore, S. P. (2025) · Indian Journal of Tuberculosis · doi:10.1016/j.ijtb.2025.10.006 · Cited by 1

Brain disease diagnosis using federated deep learning

Salam, M. A., Atef, O., Salam, N. A., & Aldawsari, M. (2026) · PeerJ Computer Science · doi:10.7717/peerj-cs.3545 · Cited by 1

Multi-client federated graph learning with dual-atlas dynamics and cluster-guided aggregation for rs-fMRI diagnosis

Guo, J., Jing, N., Zhang, M., Wang, Y., Bai, R., & Chen, Y. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110071 · Cited by 1

Federated Learning Applications in Healthcare Informatics: A Comprehensive Review

Howlader, S. M. R. K., Liu, L., Chen, X., Wu, H., Yuan, B., & Bhattacharjee, A. (2026) · ACM Computing Surveys · doi:10.1145/3809485 · Cited by 2

Fv‐SFL: A Contrastive Learning‐Based Feature Sharing Method for Reducing the Effect of Label Skewed Data Heterogeneity in Federated Medical Imaging

Panda, S., Pareek, V., & Saxena, S. (2025) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.8379 · Cited by 1

Solving Class Imbalance in Medical Image Classification Based on Federated Learning

Zhu, M. (2025) · International Conference on Generative Artificial Intelligence and Information Security (GAIIS) · doi:10.1145/3728725.3728811 · Cited by 1

FedURR

Gao, H., & Liu, Y. (2021) · doi:10.1145/3486182.3493913 · Cited by 1

2021 Index IEEE Journal of Biomedical and Health Informatics Vol. 25

(2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3140980

Artificial Intelligence Registration of Image Series Based on Multiple Features

Li, Z., Kong, D., & Zheng, Y. (2022) · Traitement du signal · doi:10.18280/ts.390122

Federated Learning Based on Feature Fusion

Cao, J., & Chen, Z. (2024) · International Conference on Neural Networks, Information and Communication Engineering (NNICE) · doi:10.1109/nnice61279.2024.10498478

SecureMed: Federated learning empowered approach for securing medical data

Makkar, A. (2024) · International Conference on Soft Computing & Machine Intelligence (ISCMI) · doi:10.1109/iscmi63661.2024.10851534

Cluster Federated Learning with Intra-Cluster Correction

Yang, Y., Ma, L., Fan, L., & Xie, T. (2025) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2025.064103

FedCIPP: A Novel Full-Lifecycle Intellectual Property Protection Framework for Federated Learning

He, J., Chen, X., Qian, J., Wang, X., & Mi, H. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-8197-6_12

Enhancing Federated Learning in IoT: A Quality‐Based Incentive Mechanism With Stackelberg Game Modelling

Li, Q., Zhao, H., Wang, Q., Zhang, W., Chen, Y., & Hu, Z. (2026) · IET Communications · doi:10.1049/cmu2.70139

APB‐FLDPA: Adaptive Personalized Blockchain‐Federated Learning With Differential Privacy and Attention for Privacy‐Preserving Healthcare Analytics

Chowdhury, M. K. H., Mondal, P. K., Mozumder, M. A. I., Kim, H. C., & Byeon, H. (2026) · Healthcare Technology Letters · doi:10.1049/htl2.70079 · Cited by 1

Federated learning in healthcare: Datasets, approaches and challenges

Jewalikar, A., Khan, R. A. H., & Mane, D. (2026) · AIP conference proceedings · doi:10.1063/5.0329127

Enhancing Federated Learning Privacy Through Encrypted Computation

K, A. K., Manoj, A., Kunjumon, A., & Nair, J. J. (2026) · Procedia Computer Science · doi:10.1016/j.procs.2026.06.408

Federated Learning for Rare Disease Diagnosis and Research: A Systematic Review of Methods for Handling Extreme Data Scarcity, Class Imbalance, and Site Heterogeneity

Bianchi, L., Rossi, M., & Romano, G. (2026) · Journal of Artificial Intelligence for Healthcare Systems · doi:10.68159/b293037132

Blockchain-enabled differentially private federated learning for secure and trustworthy healthcare data management

Bathli, N., Mohan, T., & Patil, S. D. (2026) · Sustainable Computing Informatics and Systems · doi:10.1016/j.suscom.2026.101489

HCS-Net: A Hybrid ConvNeXt-Nano-Swin Transformer-Tiny with bottleneck fusion and residual MLP for patient-wise skin cancer classification

Singh, R., Pateriya, R. K., & Singh, S. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.111580

Federated learning in cancer imaging: a comprehensive review and future outlook

Shi, Y., Li, W., & Cai, J. (2026) · Frontiers in Radiology · doi:10.3389/fradi.2026.1976540

CCVA-FL: Cross-Client Variations Adaptive Federated Learning for Medical ImagingPreprint

Gupta, S., & Sethi, A. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2407.11652

Customized Federated Learning for Multi-Source Decentralized Medical Image Classification

Wicaksana, J., Yan, Z., Yang, X. Y., Liu, Y., Fan, L., & Cheng, K.-T. T. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3198440 · Cited by 56

Multi-modal personalized federated learning with adaptive differential privacy for medical image classification and a privacy-preserving approach

Adhi Siva, M., & Chowdhary, C. L. (2026) · Scientific Reports · doi:10.1038/s41598-026-49896-z · Cited by 2

FedCNNAvg: Federated Learning for Preserving-Privacy of Multi-clients Decentralized Medical Image Classification

Chanda, C., Murmu, A., & Kumar, P. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-6755-1_19 · Cited by 7

A novel federated learning framework for medical imaging: Resource‐efficient approach combining PCA with early stopping

Nanekaran, N. P., & Ukwatta, E. (2025) · Medical Physics · doi:10.1002/mp.18064 · Cited by 8