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Experiments of Federated Learning for COVID-19 Chest X-ray Images
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“Similarly, Zhang et al. [24] and Yan et al. [29] used X-ray and CT image data for different Convolutional Neural Network (CNN) architectures in FL settings.”
From A systematic review on federated learning in medical image analysis (2023) · cites this paper as [29]
In the citing paper
“Yan et al. [29] presented their results using sensitivity, their highest score was 91.26%.”
From A systematic review on federated learning in medical image analysis (2023) · cites this paper as [29]
In the citing paper
“FL for COVID-19 detection model using”
From A systematic review on federated learning in medical image analysis (2023) · cites this paper as [29]
In the citing paper
“The experimental results show that ResNet-18 has the best performance in training both with FL and without FL approaches, while ResNeXt shows the highest efficiency on images with COVID-19 labels.”
From Handling privacy-sensitive medical data with federated learning: Challenges and future directions (2023) · cites this paper as [49]
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RetractedBAFL: Federated Learning with Base Ablation for Cost Effective Communication
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Paradigm Shift Towards Federated Learning for COVID-19 Detection: A Survey
Krithika, L. B. (2023) · Iraqi Journal of Science · doi:10.24996/ijs.2023.64.7.37 · Cited by 4
Detection of Covid‐19 disease by using privacy‐aware artificial intelligence system
İSMETOĞLU, A., & Canbay, Y. (2024) · Security and Privacy · doi:10.1002/spy2.434 · Cited by 3
Empowering Pandemic Response with Federated Learning for Protein Sequence Data Analysis
Chourasia, P., Tayebi, Z., Ali, S., & Patterson, M. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191721 · Cited by 3
Towards Enhanced Cyberbullying Detection: A Unified Framework with Transfer and Federated Learning
Kumari, C., & Kaur, M. (2025) · Systems · doi:10.3390/systems13090818 · Cited by 2
Firdaus, N., & Raza, Z. (2026) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-025-02875-8 · Cited by 2
Jin, Y., Zhu, H., Xu, J., & Chen, Y. (2022) · Machine learning · doi:10.1007/978-981-19-7083-2_4 · Cited by 2
PedFed: A performance evaluation-driven federated learning framework for efficient communication
Niu, K., Tai, W., Peng, X., Guo, Z., Zhang, C., & Li, H. (2024) · Advances in Complex Systems · doi:10.1142/s1793962324400014 · Cited by 2
Souza, R., Stanley, E. A. M., Winder, A. J., Kang, C., Amador, K., Ohara, E. Y., Dagasso, G., Camicioli, R. M., Monchi, O., Ismail, Z., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01499-0 · Cited by 3
Panday, A. (2020) · doi:10.31224/osf.io/z9bfv · Cited by 2
Federated Autonomous Deep Learning for Distributed Healthcare System
Pujahari, R. M., Khan, R., & Yadav, S. P. (2025) · Wiley eBooks · doi:10.1002/9781394271382.ch2 · Cited by 2
A Federated Learning Approach to Bone Metastasis Prediction Using Convolutional Neural Network
Ali, S. M., Eunus, S. I., Bushra, T. A., Mehedi, M. H. K., & Rasel, A. A. (2023) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccit60459.2023.10441154 · Cited by 2
AFL-CS: Asynchronous Federated Learning with Cosine Similarity-based Penalty Term and Aggregation
Yan, B., Jiang, X., Chen, Y., Gao, C., & Liu, X. (2023) · IEEE International Conference on Parallel and Distributed Systems (ICPADS) · doi:10.1109/icpads60453.2023.00016 · Cited by 2
Self-citation
Metadata
- Authors
- Yan, B., Wang, J., Cheng, J., Zhou, Y., Zhang, Y., Yang, Y., Liu, L., Zhao, H., Wang, C., & Liu, B.
- Affiliations
- Hainan University (CN)
- University of Chinese Academy of Sciences (CN)
- Venue
- Communications in Computer and Information Science
- Publisher
- Springer International Publishing
- Published
- 2021
- Pages
- 41-53
- ISSN
- 1865-0929 (ISSN-L)
- 1865-0937
- OpenAlex
- W3183916646
- Cited by
- 122
- References
- 20
- Citations by year
- 2026: 4 · 2025: 16 · 2024: 20 · 2023: 25 · 2022: 33 · 2021: 21
- FWCI
- 31.11
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Communications in computer and information science (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- federated learning, COVID-19 detection, chest X-ray images, privacy-preserving machine learning, data silos, health data sharing, MobileNetV2, ResNet-18, ResNeXt, COVID-NET, model performance comparison
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