A comparative study of federated learning methods for COVID-19 detection

A comparative study of federated learning methods for COVID-19 detection

Abstract Deep learning has proven to be highly effective in diagnosing COVID-19; however, its efficacy is contingent upon the availability of extensive data for model training. The data sharing among hospitals, which is crucial for training robust models, is often restricted by privacy regulations....

Full description

Bibliographic Details
Main Authors:	Erfan Darzi, Nanna M. Sijtsema, P. M. A. van Ooijen
Format:	Article
Language:	English
Published:	Nature Portfolio 2024-02-01
Series:	Scientific Reports
Subjects:	Federated learning Medical image analysis COVID-19 Privacy preserving machine learning
Online Access:	https://doi.org/10.1038/s41598-024-54323-2

Similar Items

Benchmarking federated strategies in Peer-to-Peer Federated learning for biomedical data
by: Jose L. Salmeron, et al.
Published: (2023-06-01)

Applications and Challenges of Federated Learning Paradigm in the Big Data Era with Special Emphasis on COVID-19
by: Abdul Majeed, et al.
Published: (2022-10-01)

Federated Learning to Safeguard Patients Data: A Medical Image Retrieval Case
by: Gurtaj Singh, et al.
Published: (2023-01-01)

Privacy-Preserving Federated Learning Using Homomorphic Encryption
by: Jaehyoung Park, et al.
Published: (2022-01-01)

Fostering Trustworthiness of Federated Learning Ecosystem through Realistic Scenarios
by: Athanasios Psaltis, et al.
Published: (2023-06-01)

Iterative and mixed-spaces image gradient inversion attack in federated learning
by: Linwei Fang, et al.
Published: (2024-04-01)

Privacy-Preserving Data Aggregation Scheme Based on Federated Learning for IIoT
by: Fan Hongbin, et al.
Published: (2023-01-01)

Federated Learning-Based Privacy-Preserving Data Aggregation Scheme for IIoT
by: Hongbin Fan, et al.
Published: (2023-01-01)

Distributed Fire Detection and Localization Model Using Federated Learning
by: Yue Hu, et al.
Published: (2023-03-01)

Federated Learning with Dynamic Model Exchange
by: Hannes Hilberger, et al.
Published: (2022-05-01)

Reviewing Federated Machine Learning and Its Use in Diseases Prediction
by: Mohammad Moshawrab, et al.
Published: (2023-02-01)

Privacy-preserving federated machine learning on FAIR health data: A real-world application
by: A. Anil Sinaci, et al.
Published: (2024-12-01)

FL-ODP: An Optimized Differential Privacy Enabled Privacy Preserving Federated Learning
by: Maria Iqbal, et al.
Published: (2023-01-01)

Homomorphic Encryption-Based Federated Privacy Preservation for Deep Active Learning
by: Hendra Kurniawan, et al.
Published: (2022-10-01)

Dynamic Asynchronous Anti Poisoning Federated Deep Learning with Blockchain-Based Reputation-Aware Solutions
by: Zunming Chen, et al.
Published: (2022-01-01)

Hierarchical federated learning with global differential privacy
by: Youqun Long, et al.
Published: (2023-04-01)

Advancing Federated Learning Through Novel Mechanism for Privacy Preservation in Healthcare Applications
by: Mohammed Abaoud, et al.
Published: (2023-01-01)

A Communication-Efficient, Privacy-Preserving Federated Learning Algorithm Based on Two-Stage Gradient Pruning and Differentiated Differential Privacy
by: Yong Li, et al.
Published: (2023-11-01)

Federated Learning-Based Insulator Fault Detection for Data Privacy Preserving
by: Zhirong Luan, et al.
Published: (2023-06-01)

Efficient privacy-preserving federated learning method for Internet of Ships
by: Zehui ZHANG, et al.
Published: (2022-12-01)

Comparative Analysis of Membership Inference Attacks in Federated and Centralized Learning
by: Ali Abbasi Tadi, et al.
Published: (2023-11-01)

A Systematic Review on Federated Learning in Medical Image Analysis
by: Md Fahimuzzman Sohan, et al.
Published: (2023-01-01)

Joining Federated Learning to Blockchain for Digital Forensics in IoT
by: Wejdan Almutairi, et al.
Published: (2023-08-01)

A federated learning framework for pneumonia image detection using distributed data
by: Amer Kareem, et al.
Published: (2023-12-01)

Blockchain-based privacy-preserving multi-tasks federated learning framework
by: Yunyan Jia, et al.
Published: (2024-12-01)

PPChain: A Blockchain for Pandemic Prevention and Control Assisted by Federated Learning
by: Tianruo Cao, et al.
Published: (2023-08-01)

FedOpt: Towards Communication Efficiency and Privacy Preservation in Federated Learning
by: Muhammad Asad, et al.
Published: (2020-04-01)

LAFD: Local-Differentially Private and Asynchronous Federated Learning With Direct Feedback Alignment
by: Kijung Jung, et al.
Published: (2023-01-01)

Federated Learning Scheme Based on Secure Multi-party Computation and Differential Privacy
by: TANG Ling-tao, WANG Di, ZHANG Lu-fei, LIU Sheng-yun
Published: (2022-09-01)

Federated Learning Based Privacy Ensured Sensor Communication in IoT Networks: A Taxonomy, Threats and Attacks
by: Sheikh Imroza Manzoor, et al.
Published: (2023-01-01)

A Novel Federated Edge Learning Approach for Detecting Cyberattacks in IoT Infrastructures
by: Sidra Abbas, et al.
Published: (2023-01-01)

Genetic Clustered Federated Learning for COVID-19 Detection
by: Dasaradharami Reddy Kandati, et al.
Published: (2022-08-01)

A systematic review of privacy-preserving methods deployed with blockchain and federated learning for the telemedicine
by: Madhuri Hiwale, et al.
Published: (2023-11-01)

UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework
by: Biyao Che, et al.
Published: (2024-01-01)

SHFL: K-Anonymity-Based Secure Hierarchical Federated Learning Framework for Smart Healthcare Systems
by: Muhammad Asad, et al.
Published: (2022-11-01)

Empowering Precision Medicine: Unlocking Revolutionary Insights through Blockchain-Enabled Federated Learning and Electronic Medical Records
by: Aitizaz Ali, et al.
Published: (2023-08-01)

Expand and Shrink: Federated Learning with Unlabeled Data Using Clustering
by: Ajit Kumar, et al.
Published: (2023-11-01)

Communication-Efficient Vertical Federated Learning
by: Afsana Khan, et al.
Published: (2022-08-01)

Federated Data Augmentation Algorithm for Non-independent and Identical Distributed Data
by: QU Xiang-mou, WU Ying-bo, JIANG Xiao-ling
Published: (2022-12-01)

Peer-to-Peer Federated Learning for COVID-19 Detection Using Transformers
by: Mohamed Chetoui, et al.
Published: (2023-05-01)