Federated learning for medical image analysis: A survey

H Guan, PT Yap, A Bozoki, M Liu - Pattern Recognition, 2024 - Elsevier
Abstract Machine learning in medical imaging often faces a fundamental dilemma, namely,
the small sample size problem. Many recent studies suggest using multi-domain data …

A survey on intelligent Internet of Things: Applications, security, privacy, and future directions

O Aouedi, TH Vu, A Sacco, DC Nguyen… - … surveys & tutorials, 2024 - ieeexplore.ieee.org
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …

Federated distillation and blockchain empowered secure knowledge sharing for internet of medical things

X Zhou, W Huang, W Liang, Z Yan, J Ma, Y Pan… - Information …, 2024 - Elsevier
With the development of Internet of Things (IoT) and Artificial Intelligence (AI) technologies,
smart services have penetrated into every aspect of our daily lives, including the medical …

[HTML][HTML] Quantum-empowered federated learning and 6G wireless networks for IoT security: Concept, challenges and future directions

D Javeed, MS Saeed, I Ahmad, M Adil, P Kumar… - Future Generation …, 2024 - Elsevier
Abstract The Internet of Things (IoT) has revolutionized various sectors by enabling
seamless device interaction. However, the proliferation of IoT devices has also raised …

Generative AI for the optimization of next-generation wireless networks: Basics, state-of-the-art, and open challenges

F Khoramnejad, E Hossain - IEEE Communications Surveys & …, 2025 - ieeexplore.ieee.org
Next-generation (xG) wireless networks, with their complex and dynamic nature, present
significant challenges to using traditional optimization techniques. Generative Artificial …

Federated learning for the internet-of-medical-things: A survey

VK Prasad, P Bhattacharya, D Maru, S Tanwar… - Mathematics, 2022 - mdpi.com
Recently, in healthcare organizations, real-time data have been collected from connected or
implantable sensors, layered protocol stacks, lightweight communication frameworks, and …

Artificial intelligence for clinical decision support for monitoring patients in cardiovascular ICUs: a systematic review

S Moazemi, S Vahdati, J Li, S Kalkhoff… - Frontiers in …, 2023 - frontiersin.org
Background Artificial intelligence (AI) and machine learning (ML) models continue to evolve
the clinical decision support systems (CDSS). However, challenges arise when it comes to …

Federated semi-supervised learning for medical image segmentation via pseudo-label denoising

L Qiu, J Cheng, H Gao, W **ong… - IEEE journal of …, 2023 - ieeexplore.ieee.org
Distributed big data and digital healthcare technologies have great potential to promote
medical services, but challenges arise when it comes to learning predictive model from …

Privacy preservation for federated learning in health care

S Pati, S Kumar, A Varma, B Edwards, C Lu, L Qu… - Patterns, 2024 - cell.com
Artificial intelligence (AI) shows potential to improve health care by leveraging data to build
models that can inform clinical workflows. However, access to large quantities of diverse …

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

C Dhasaratha, MK Hasan, S Islam… - CAAI Transactions …, 2024 - Wiley Online Library
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector
with rapid potential proof for decentralised communication systems that have been applied …