This textbook provides an in-depth exploration of how machine learning algorithms can be effectively applied to detect and classify heart disease. It bridges the gap between healthcare and computational intelligence by presenting theoretical foundations, practical implementations, and real-world applications of machine learning in cardiology. Starting with an overview of cardiovascular diseases and their global impact, the book delves into essential medical features and datasets relevant to heart disease. It then systematically explores various machine learning techniques-including decision...

Fog computing is an emerging paradigm in the field of distributed computing that acts as an extension of cloud computing. Unlike the traditional cloud model, which relies on centralized data centres located far from the end users, fog computing brings computation, storage, and networking services closer to the physical location of data sources and users. This proximity to end devices significantly reduces communication latency, enhances data processing speed, and supports real-time decision-making, which is critical in applications that demand immediate responses, such as autonomous vehicles,...