On COVID-19 Prediction Using Asynchronous Federated Learning-Based Agile Radiograph Screening Booths

Automated detection of COVID-19 cases using deep neural networks with X-ray images

Öztürk, T., Talo, M., Yildirim, E. A., Baloğlu, U. B., Yıldırım, Ö., & Acharya, U. R. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.103792 · Cited by 2,607 · see citing works

Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networks

Narin, A., Kaya, C., & Pamuk, Z. (2021) · Pattern Analysis and Applications · doi:10.1007/s10044-021-00984-y · Cited by 2,054 · see citing works

Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network

Abbas, A., Abdelsamea, M. M., & Gaber, M. M. (2020) · Applied Intelligence · doi:10.1007/s10489-020-01829-7 · Cited by 1,142 · see citing works

A Speculative Study on 6G

Tariq, F., Khandaker, M. R. A., Wong, K.-K., Imran, M. A., Bennis, M., & Debbah, M. (2020) · IEEE Wireless Communications · doi:10.1109/mwc.001.1900488 · Cited by 1,014 · see citing works

Radiology Perspective of Coronavirus Disease 2019 (COVID-19): Lessons From Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome

Hosseiny, M., Kooraki, S., Gholamrezanezhad, A., Reddy, S., & Myers, L. (2020) · American Journal of Roentgenology · doi:10.2214/ajr.20.22969 · Cited by 458 · see citing works

Security and Privacy-Preserving Challenges of e-Health Solutions in Cloud Computing

Chenthara, S., Ahmed, K. E. U., Wang, H., & Whittaker, F. (2019) · IEEE Access · doi:10.1109/access.2019.2919982 · Cited by 350 · see citing works

Radiology Department Preparedness for COVID-19: <i>Radiology</i> Scientific Expert Review Panel

Mossa-Basha, M., Meltzer, C. C., Kim, D. C., Tuite, M. J., Kolli, K. P., & Tan, B. S. (2020) · Radiology · doi:10.1148/radiol.2020200988 · Cited by 324 · see citing works

DL-CRC: Deep Learning-Based Chest Radiograph Classification for COVID-19 Detection: A Novel Approach

Sakib, S., Tazrin, T., Fouda, M. M., Fadlullah, Z. M., & Guizani, M. (2020) · IEEE Access · doi:10.1109/access.2020.3025010 · Cited by 164 · see citing works

HCP: Heterogeneous Computing Platform for Federated Learning Based Collaborative Content Caching Towards 6G Networks

Fadlullah, Z. M., & Kato, N. (2020) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2020.2986238 · Cited by 137 · see citing works

Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly DetectionPreprint

Zhang, J., Xie, Y., Pang, G., Liao, Z., Verjans, J. W. H., Li, W., Sun, Z., He, J., Li, Y., Shen, C., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.12338 · Cited by 122 · see citing works

Leveraging Tactile Internet Cognizance and Operation via IoT and Edge Technologies

Oteafy, S., & Hassanein, H. S. (2018) · Proceedings of the IEEE · doi:10.1109/jproc.2018.2873577 · Cited by 61 · see citing works

Is Immersive Virtual Reality the Ultimate Interface for 3D Animators?

Lamberti, F., Cannavò, A., & Montuschi, P. (2020) · Computer · doi:10.1109/mc.2019.2908871 · Cited by 24 · see citing works

Chest imaging in patients with suspected COVID-19

Adams, S., & Dennie, C. J. (2020) · Canadian Medical Association Journal · doi:10.1503/cmaj.200626 · Cited by 5 · see citing works

Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions

Rauniyar, A., Hagos, D. H., Jha, D., Håkegård, J. E., Bagci, U., Rawat, D. B., & Vlassov, V. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3329061 · Cited by 315 · see citing works

A systematic review on federated learning in medical image analysis

Sohan, M. F., & Basalamah, A. (2023) · IEEE Access · doi:10.1109/access.2023.3260027 · Cited by 114 · see citing works

Federated learning for medical imaging radiology

Rehman, M. H. U., Pinaya, W. H. L., Nachev, P., Teo, J., Sebastien Ourselin, A., & Cardoso, M. J. (2023) · British Journal of Radiology · doi:10.1259/bjr.20220890 · Cited by 118 · see citing works

On Smart IoT Remote Sensing over Integrated Terrestrial-Aerial-Space Networks: An Asynchronous Federated Learning Approach

Fadlullah, Z. M., & Kato, N. (2021) · IEEE Network · doi:10.1109/mnet.101.2100125 · Cited by 68 · see citing works

Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments

Majeed, A., & Hwang, S. O. (2021) · Symmetry · doi:10.3390/sym14010016 · Cited by 62 · see citing works

Data-Aware Device Scheduling for Federated Edge Learning

Taïk, A., Mlika, Z., & Cherkaoui, S. (2021) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2021.3100574 · Cited by 54 · see citing works

Joint Self-Organizing Maps and Knowledge-Distillation-Based Communication-Efficient Federated Learning for Resource-Constrained UAV-IoT Systems

Gad, G., Farrag, A., Aboulfotouh, A., Bedda, K., Fadlullah, Z. M., & Fouda, M. M. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3349295 · Cited by 40 · see citing works

Independent and Identically Distributed (IID) Data Assessment in Federated Learning

Arafeh, M., Hammoud, A., Otrok, H., Mourad, A., Talhi, C., & Dziong, Z. (2022) · Globecom · doi:10.1109/globecom48099.2022.10001718 · Cited by 38 · see citing works

Deep Learning Models for Magnetic Cardiography Edge Sensors Implementing Noise Processing and Diagnostics

Sakib, S., Fouda, M. M., Al‐Mahdawi, M., Mohsen, A. S., Oogane, M., Ando, Y., & Fadlullah, Z. M. (2021) · IEEE Access · doi:10.1109/access.2021.3138976 · Cited by 28 · see citing works

An Explainable AI Model for Interpretable Lung Disease Classification

Pitroda, V., Fouda, M. M., & Fadlullah, Z. M. (2021) · IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) · doi:10.1109/iotais53735.2021.9628573 · Cited by 27 · see citing works

A Survey on AI Techniques for Thoracic Diseases Diagnosis Using Medical Images

Mostafa, F. A., Elrefaei, L. A., Fouda, M. M., & Hossam, A. (2022) · Diagnostics · doi:10.3390/diagnostics12123034 · Cited by 26 · see citing works

Adaptive 5G-and-beyond network-enabled interpretable federated learning enhanced by neuroevolution

Cao, B., Zhao, J., Liu, X., & Li, Y. (2024) · Science China Information Sciences · doi:10.1007/s11432-023-4011-4 · Cited by 24 · see citing works

Anti-Jamming Strategy for Federated Learning in Internet of Medical Things: A Game Approach

Ruby, R., Yang, H., & Wu, K. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3183644 · Cited by 20 · see citing works

Joint Knowledge Distillation and Local Differential Privacy for Communication-Efficient Federated Learning in Heterogeneous Systems

Gad, G., Fadlullah, Z. M., Fouda, M. M., Ibrahem, M. I., & Nasser, N. (2023) · Globecom · doi:10.1109/globecom54140.2023.10437358 · Cited by 19 · see citing works

Centralized and Federated Learning for COVID-19 Detection With Chest X-Ray Images: Implementations and Analysis

Naz, S., Phan, K. T., & Chen, Y. P. (2024) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2024.3371222 · Cited by 17 · see citing works

Communication-Efficient Federated Learning in Drone-Assisted IoT Networks: Path Planning and Enhanced Knowledge Distillation Techniques

Gad, G., Farrag, A., Fadlullah, Z. M., & Fouda, M. M. (2023) · IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) · doi:10.1109/pimrc56721.2023.10294036 · Cited by 12 · see citing works

A Circuit-embedded Reservoir Computer for Smart Noise Reduction of MCG Signals

Shakya, B., Fouda, M. M., Chiu, S. C., & Fadlullah, Z. M. (2021) · IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) · doi:10.1109/iotais53735.2021.9628824 · Cited by 5 · see citing works

TWAFR-GRU: An Integrated Model for Real-time Charging Station Occupancy Prediction

Chen, Q., Liu, S., Qu, H., Zhu, R., & You, L. (2022) · IEEE Smart World Congress (SWC) · doi:10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00233 · Cited by 3 · see citing works

Noise processing and diagnostics of a spintronic-based IOT sensor for magnetocardiography application using SpintronCardioNet

Sinha, R., & Kaur, J. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19378-3 · Cited by 2 · see citing works

REDUS: Adaptive Resampling for Efficient Deep Learning in Centralized and Federated IoT Networks

Gad, E., Gad, G., Fouda, M. M., Ibrahem, M. I., Ismail, M., & Fadlullah, Z. M. (2025) · International Conference on Communications · doi:10.1109/icc52391.2025.11161717 · Cited by 2 · see citing works

Asynchronous Federated Learning: Methods and applications

Liu, Y. (2024) · Applied and Computational Engineering · doi:10.54254/2755-2721/39/20230588 · Cited by 1 · see citing works

Joint Provisioning of QoS and Privacy with Federated Learning

Fadlullah, Z. M., & Fouda, M. M. (2022) · Springer eBooks · doi:10.1007/978-3-031-04321-5_14 · Cited by 1 · see citing works

Federated Learning-Based Techniques for COVID-19 Detection—A Systematic Review

Hosmani, B., Shariff, M. J., & Geetha, J. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-6586-1_42

Detection of Covid-19 at early symptoms with higher accuracy using novel chest x-ray images using Alexnet network comparing with VGG16 network

Arshathraj, A., & Premkumar, S. (2025) · AIP conference proceedings · doi:10.1063/5.0278972

Federated Learning in the Healthcare Industry

Mondal, R. (2025) · Studies in systems, decision and control · doi:10.1007/978-3-031-99270-4_2

Federated learning for COVID-19 screening from Chest X-ray images

Feki, I., Ammar, S., Kessentini, Y., & Muhammad, K. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2021.107330 · Cited by 278 · see citing works

Enhanced COVID-19 Detection and Privacy Preserving Using Federated Learning

Pravallika, P., Gnanasri, V., Gireesh, M., Reddy, A. A., Kalpana, V., & Chowdary, J. S. (2023) · International Conference on Inventive Research in Computing Applications (ICIRCA) · doi:10.1109/icirca57980.2023.10220772 · Cited by 4 · see citing works

Near Real-Time Federated Machine Learning Approach Over Chest Computed Tomography for COVID-19 Diagnosis

Cao, Y. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-1166-8_3 · Cited by 4 · see citing works

ResNetFed: Federated Deep Learning Architecture for Privacy-Preserving Pneumonia Detection from COVID-19 Chest Radiographs

Riedel, P., von Schwerin, R., Schaudt, D., Hafner, A., & Späte, C. (2023) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-023-00132-7 · Cited by 24 · see citing works

DPCOVID: Privacy-Preserving Federated Covid-19 DetectionPreprint

Ho, T.-T., & Yennun-Huang (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.13760 · Cited by 2 · see citing works