J Zhu, J Cao, D Saxena, S Jiang, H Ferradi - ACM Computing Surveys, 2023 - dl.acm.org
Federated learning is a privacy-preserving machine learning technique that trains models across multiple devices holding local data samples without exchanging them. There are …
In this article, we present a comprehensive study with an experimental analysis of federated deep learning approaches for cyber security in the Internet of Things (IoT) applications …
WY Ng, TE Tan, PVH Movva, AHS Fang… - The Lancet Digital …, 2021 - thelancet.com
The COVID-19 pandemic has had a substantial and global impact on health care, and has greatly accelerated the adoption of digital technology. One of these emerging digital …
Federated learning (FL) has experienced a boom in recent years, which is jointly promoted by the prosperity of machine learning and Artificial Intelligence along with emerging privacy …
S Aminizadeh, A Heidari, S Toumaj, M Darbandi… - Computer methods and …, 2023 - Elsevier
Medical data processing has grown into a prominent topic in the latest decades with the primary goal of maintaining patient data via new information technologies, including the …
The federated learning technique (FL) supports the collaborative training of machine learning and deep learning models for edge network optimization. Although a complex edge …
Recently, innovations in the Internet of Medical Things (IoMT), information and communication technologies, and machine learning (ML) have enabled smart healthcare …
Recent technological developments, such as the Internet of Things (IoT), artificial intelligence, edge, and cloud computing, have paved the way in transforming traditional …
M Chen, P Li, R Wang, Y Xiang, Z Huang… - Advanced …, 2022 - Wiley Online Library
The application of wearable devices is promoting the development toward digitization and intelligence in the field of health. However, the current smart devices centered on human …