Integrating Artificial Intelligence (AI) in healthcare represents a transformative shift with
substantial potential for enhancing patient care. This paper critically examines this …

Cutting-edge technologies have been widely employed in healthcare delivery, resulting in
transformative advances and promising enhanced patient care, operational efficiency, and …

During the COVID-19 pandemic, the urgency of effective testing strategies had never been
more apparent. The fusion of Artificial Intelligence (AI) and Machine Learning (ML) models …

Abstract The Internet of Medical Things (IoMT) revolutionizes healthcare, enhances patient
care, and optimizes workflows. However, the integration of IoMT introduces concerns related …

Federated learning protects sensitive data during AI model training, enabling collaboration
without sharing raw data. Ensuring fairness and addressing un-shared decisions are crucial …

Despite the need for data from multiple sources in machine learning, privacy constraints limit
data sharing. Federated Learning (FL) addresses this by allowing clients to share locally …

This examination explores joined picking up gathering appraisals, unequivocally United
Averaging (FedAvg), Weighted Consolidated Averaging (FedAvg-W), Bound together …

It is becoming more and more important for healthcare providers to protect the integrity and
security of sensitive medical data as they use cloud computing for data processing and …

Healthcare 5.0 signifies a radical paradigm shift in the healthcare sector in an era of
technology that is advancing at an exponential rate. In this chapter, the author goes into the …

This project greatly contributes to the integration of IOT systems for the actual development
of fall detection mechanisms with advanced RL algorithms. Hence the IOT system mainly …