[HTML][HTML] Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review

S Rani, A Kataria, S Kumar, P Tiwari - Knowledge-based systems, 2023 - Elsevier
Recent developments in the Internet of Things (IoT) and various communication
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …

Federated learning in edge computing: a systematic survey

HG Abreha, M Hayajneh, MA Serhani - Sensors, 2022 - mdpi.com
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …

A review on machine learning styles in computer vision—techniques and future directions

SV Mahadevkar, B Khemani, S Patil, K Kotecha… - Ieee …, 2022 - ieeexplore.ieee.org
Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …

Federated learning for medical applications: A taxonomy, current trends, challenges, and future research directions

A Rauniyar, DH Hagos, D Jha… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
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 …

Integrated CNN and federated learning for COVID-19 detection on chest X-ray images

Z Li, X Xu, X Cao, W Liu, Y Zhang… - … /ACM Transactions on …, 2022 - ieeexplore.ieee.org
Currently, Coronavirus Disease 2019 (COVID-19) is still endangering world health and
safety and deep learning (DL) is expected to be the most powerful method for efficient …

Handling privacy-sensitive medical data with federated learning: challenges and future directions

O Aouedi, A Sacco, K Piamrat… - IEEE journal of …, 2022 - ieeexplore.ieee.org
Recent medical applications are largely dominated by the application of Machine Learning
(ML) models to assist expert decisions, leading to disruptive innovations in radiology …

Advancing pandemic preparedness in healthcare 5.0: A survey of federated learning applications

S Hamood Alsamhi, A Hawbani… - Advances in Human …, 2023 - Wiley Online Library
The intersection of Federated Learning (FL) and Healthcare 5.0 promises a transformative
shift towards a more resilient future, particularly concerning pandemic preparedness. Within …

A systematic review on federated learning in medical image analysis

MF Sohan, A Basalamah - IEEE Access, 2023 - ieeexplore.ieee.org
Federated Learning (FL) obtained a lot of attention to the academic and industrial
stakeholders from the beginning of its invention. The eye-catching feature of FL is handling …

A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening …

AAS Soltan, A Thakur, J Yang, A Chauhan… - The Lancet Digital …, 2024 - thelancet.com
Background Multicentre training could reduce biases in medical artificial intelligence (AI);
however, ethical, legal, and technical considerations can constrain the ability of hospitals to …

FedSGDCOVID: Federated SGD COVID-19 detection under local differential privacy using chest X-ray images and symptom information

TT Ho, KD Tran, Y Huang - Sensors, 2022 - mdpi.com
Coronavirus (COVID-19) has created an unprecedented global crisis because of its
detrimental effect on the global economy and health. COVID-19 cases have been rapidly …