The rapid advancement of technology has ushered in a new era of healthcare, termed
Healthcare 5.0, marked by the integration of Artificial Intelligence (AI), Digital Twin …

Modern healthcare organizations face various cy-bersecurity threats due to the digitization of
their systems. These threats include data breaches, ransomware attacks, and unauthorized …

This paper investigates the synergy between 6G and AI. It argues that they can unlock future
horizons, by discussing how they can address future challenges in healthcare …

There is a strong need for having an operative security framework which can help in making
IoT (Internet of Things) devices more secure and reliable which can further protect from …

This paper presents the use of federated learning (FL) in healthcare to improve the efficiency
and accuracy of medical diagnosis while addressing privacy concerns related to medical …

Abstract The Internet of Things (IoT) is a rapidly expanding network of interconnected things
that use embedded sensors to gather and share data in real‐time. IoT technologies have …

This paper introduces an innovative method for fine-tuning a larger multi-label model for
abnormality detection, utilizing a smaller trainer and advanced knowledge distillation …

Federated learning, an innovative methodology that enables clients to train a global model
collectively without disclosing raw data, protects data privacy when it comes to training …

Federated learning is a distributed machine learning framework that solves data security
and data island problems faced by artificial intelligence. However, federated learning …

In this paper, we present a new approach for ECG signal classification based on Federated
Unlearning (FUL) concept. In fact, the analysis and the processing of ECG signals are a key …