Federated Intelligence in Medicine

Federated Intelligence in Medicine: AI-Driven Robotics for Secure and Intelligent Healthcare Systems explores the rapidly evolving field where medical robotics intersects with cutting-edge artificial intelligence and secure data-sharing technologies. Covering a comprehensive range of topics, the book begins with foundational knowledge in medical robotics and Generative AI, progressing to advanced concepts such as federated learning and architectural modeling tailored for AI-driven robotic systems. Readers will explore algorithms enhancing surgical robotics, remote robotic surgeries, and human-robot interaction. The text also tackles AI-driven diagnostic robots, privacy preservation through homomorphic encryption, and differential privacy and emerging medical imaging techniques integrated with robotics. Later chapters examine the synergy of large language models, agent AI, and edge AI with robotic technologies, providing both theoretical frameworks and practical case studies that illuminate real-world applications and challenges. This book is an invaluable resource for researchers and academicians engaged in artificial intelligence, robotics, and medical technology. It also serves undergraduate and graduate students in Biomedical Engineering, Electronics and Electrical Engineering, and Computer Science and Engineering.