Edge-AI in Healthcare 1st Edition

Edge-AI in Healthcare — 1st Edition by Sonali Vyas, Akanksha Upadhyaya, Deepshikha Bhargava, and Vinod Kumar Shukla

Capture the future of healthcare where intelligent devices meet the bedside. This authoritative guide on Edge-AI in Healthcare distills cutting-edge research and practical implementations into a clear roadmap for clinicians, engineers, data scientists, and policymakers seeking real-world solutions.

Explore how on-device intelligence transforms patient care with low-latency diagnostics, continuous remote monitoring, and secure data handling at the source. The book explains core technologies—model optimization, tinyML, federated learning, sensor fusion, and secure edge architectures—paired with concrete healthcare applications such as wearable monitoring, point-of-care imaging, smart ambulances, and hospital IoT systems. Regional considerations for deployment across India, Europe, North America, and emerging markets are woven throughout, making the content globally relevant and locally actionable.

Designed for both technical and clinical audiences, the text balances theory with practical insights: implementation strategies, performance trade-offs, privacy and regulatory perspectives, and ethical considerations that matter to hospitals and healthtech startups alike. Case studies and deployment scenarios illuminate challenges and best practices for scaling edge-AI solutions in real clinical environments.

Whether you’re building next-generation medical devices, modernizing clinical workflows, or shaping digital health policy, this book equips you with the knowledge to design robust, compliant, and patient-centered edge-AI systems. Stay ahead in the rapidly evolving intersection of artificial intelligence and healthcare—add Edge-AI in Healthcare to your professional library today.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.