Häftad, Engelska, 2027
2 050 kr
Kommande
Digital Twins and Predictive Modeling in Robotic Surgery addresses the transformative convergence of digital twin technology, predictive analytics, and robotic surgery. This reference responds to the critical need for a comprehensive resource that bridges simulation science, artificial intelligence, and real-time robotic execution, facilitating enhanced surgical precision, patient-specific planning, and intraoperative decision-making. The content is organized into four parts covering foundational intelligent surgical systems, predictive modeling and simulation, clinical applications with case studies, and challenges alongside future directions. Topics include AI integration, IoT-enabled sensor networks, digital twin architectures encompassing the entire surgical ecosystem, surgical workflow modeling, risk assessment, human-robot interaction, technology acceptance, ethical and regulatory considerations. Real-world examples from smart hospitals worldwide illustrate practical implementation. This books benefits biomedical engineers, researchers, and healthcare system architects by providing interdisciplinary insights, practical implementation frameworks, and cutting-edge case studies. It supports improved surgical planning, precision, and decision-making, empowering end users to advance the adoption of intelligent, AI-powered robotic surgery systems in clinical practice and research environments.Bridges clinical, engineering, and data science domains with practical workflows and system architecturesOffers structured frameworks for virtual patient and operating room digital twin modeling and predictive analyticsIncludes expanded real-world case studies and practical implementation strategies from smart operating rooms globallyPresents dedicated chapters on technology acceptance, human-computer interaction, and ethical AI in robotic surgeryProvides insights on regulatory, validation, and clinical trial considerations for AI-enabled surgical systems
