The book explores the intersection of neuroscience, artificial intelligence, and chronomedicine in addressing complex brain diseases linked to circadian rhythm disruption. This book examines how AI-driven analytics and machine learning can decode biological rhythms, enabling the design of personalized therapeutic strategies for disorders such as Alzheimer's, Parkinson's, and other neurodegenerative conditions. It highlights innovative approaches including digital biomarkers, wearable monitoring, and computational modeling that support precision chronotherapy by aligning treatment schedules...

This book introduces a groundbreaking AI-driven framework for rapid brain imaging assessment in acute neurological conditions such as stroke, traumatic injury, and hemorrhage. Combining deep learning, edge computing, and multimodal data fusion, ARIA-NET enables real-time decision support for emergency physicians and neurologists. The book explores the system's adaptive architecture, real-time optimization, and clinical workflow integration, offering both theoretical foundations and practical implementation strategies. Through case studies and algorithmic analysis, it highlights how...