Blockchain meets federated learning in healthcare: A systematic review with challenges and opportunities
R Myrzashova, SH Alsamhi… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Recently, innovations in the Internet of Medical Things (IoMT), information and
communication technologies, and machine learning (ML) have enabled smart healthcare …
communication technologies, and machine learning (ML) have enabled smart healthcare …
Federated learning for medical applications: A taxonomy, current trends, challenges, and future research directions
With the advent of the Internet of Things (IoT), artificial intelligence (AI), machine learning
(ML), and deep learning (DL) algorithms, the landscape of data-driven medical applications …
(ML), and deep learning (DL) algorithms, the landscape of data-driven medical applications …
Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application
Blockchain technology (BT) allows market participants to keep track of digital transactions
without central recordkeeping. The features of blockchain, including decentralization …
without central recordkeeping. The features of blockchain, including decentralization …
Differential privacy in blockchain technology: A futuristic approach
Blockchain has received a widespread attention because of its decentralized, tamper-proof,
and transparent nature. Blockchain works over the principle of distributed, secured, and …
and transparent nature. Blockchain works over the principle of distributed, secured, and …
A review of medical federated learning: Applications in oncology and cancer research
A Chowdhury, H Kassem, N Padoy, R Umeton… - International MICCAI …, 2021 - Springer
Abstract Machine learning has revolutionized every facet of human life, while also becoming
more accessible and ubiquitous. Its prevalence has had a powerful impact in healthcare …
more accessible and ubiquitous. Its prevalence has had a powerful impact in healthcare …
Differential privacy model for blockchain based smart home architecture
Secure and private communications using the Internet of Things (IoT) pose several
challenges for smart home systems. In particular, data collected from IoT devices comprise …
challenges for smart home systems. In particular, data collected from IoT devices comprise …
Robust asynchronous federated learning with time-weighted and stale model aggregation
Federated Learning (FL) ensures collaborative learning among multiple clients while
maintaining data locally. However, the traditional synchronous FL solutions have lower …
maintaining data locally. However, the traditional synchronous FL solutions have lower …
[PDF][PDF] Privacy-protecting techniques for behavioral data: A survey
∗ Funded by the German Research Foundation (DFG, Deutsche Forschungsgemeinschaft)
as part of Germany's Excellence Strategy–EXC 2050/1–Project ID 390696704–Cluster of …
as part of Germany's Excellence Strategy–EXC 2050/1–Project ID 390696704–Cluster of …
Efficient and Privacy-Enhanced Asynchronous Federated Learning for Multimedia Data in Edge-based IoT
H Xiong, H Yan, MS Obaidat, J Chen, M Cao… - ACM Transactions on …, 2024 - dl.acm.org
With the rapid development of smart device technology, the current version of the Internet of
Things (IoT) is moving towards a multimedia IoT because of multimedia data. This innovative …
Things (IoT) is moving towards a multimedia IoT because of multimedia data. This innovative …
Using blockchain and distributed machine learning to manage decentralized but trustworthy disease data
Public health surveillance systems for infectious diseases, that can turn pandemic, need a
regular intervention for diagnosis, treatment and control. For an effective disease monitoring …
regular intervention for diagnosis, treatment and control. For an effective disease monitoring …