Healthcare is predominantly regarded as a crucial consideration in promoting the general
physical and mental health and well‐being of people around the world. The amount of data …

Personalised healthcare has seen significant improvements due to the introduction of health
monitoring technologies that allow wearable devices to unintrusively monitor physiological …

Abstract Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial
Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare …

Artificial intelligence (AI) has led to a high rate of development in healthcare, and good
progress has been made on many complex medical problems. However, there is a lack of …

Multimodal data fusion is a critical element of fall detection systems, as it provides more
comprehensive information than single-modal data. Yet, data heterogeneity between …

Extensive research has been conducted on healthcare technology and service
advancements during the last decade. The Internet of Medical Things (IoMT) has …

Federated learning (FL) is a distributed machine learning framework that is gaining traction
in view of increasing health data privacy protection needs. By conducting a systematic …

In this study, a weighted federated learning approach is proposed for electrocardiogram
(ECG) arrhythmia classification. The proposed approach considers the heterogeneity of data …

Abstract Internet-of-things (IoT) is a revolutionary paragon that brings automation and
easiness to human lives and improves their experience. Smart Homes, Healthcare, and …

Magnetic resonance imaging is the most generally utilized imaging methodology that
permits radiologists to look inside the cerebrum using radio waves and magnets for tumor …