Description
Smart Healthcare 2.0: Integrating Digital Twins with AI-Driven Predictive Analytics offers a groundbreaking exploration of how digital twin technology, combined with real-time sensing and predictive analytics, is transforming healthcare delivery. As the global healthcare landscape shifts toward proactive, personalized care, this book addresses the urgent need for comprehensive resources that unify artificial intelligence, Internet of Things (IoT), and biomedical engineering within the digital twin framework. It provides an essential guide for researchers, engineers, and clinicians aiming to harness virtual patient models and data-driven insights to improve health outcomes and system efficiency in the era of ubiquitous healthcare.This volume covers a wide spectrum of topics, starting with foundational concepts of digital twins in precision health and advancing through smart sensing technologies, scalable system architectures, and AI-powered predictive analytics. Readers will explore detailed discussions on edge-cloud computing, secure communication protocols including blockchain, and simulation platforms that enable virtual patient modeling. The book also addresses critical themes such as chronic disease management, emergency response optimization, ethical AI deployment, interoperability standards, and workforce readiness. Real-world case studies and future-focused chapters on cognitive twins and quantum simulation provide a rich, multidisciplinary perspective.- Bridges AI, IoT, and biomedical engineering for comprehensive digital twin healthcare system design and deployment- Offers practical frameworks for secure, scalable, and real-time patient monitoring and predictive health interventions- Integrates ethical, legal, and interoperability considerations to ensure trustworthy and clinically relevant healthcare solutions- Provides case studies and simulation tools to support research, education, and innovation in smart healthcare technologies
Table of Contents
1. Digital Twins in Precision Health: From Static Models to Adaptive Virtual Patients2. Ubiquitous Healthcare 3.0: Principles, Paradigms, and Proactive System Design3. Smart Sensing in Digital Health: Wearable and Implantable Technologies4. Architecture 3.0 for Digital Twin-Driven U-Healthcare Systems5. Predictive Analytics in Health: Models and AI-Powered Applications6. Edge-Fog-Cloud Continuum for Scalable Digital Twin Computation7. Data Fusion and Context Awareness in Digital Twin Systems8. Secure Communication 3.0 and Blockchain for Trustworthy Digital Health9. Simulation Platforms for Virtual Patients: Modeling, Testing, and Visualization10. Chronic Disease Management 3.0: Twin-Based Continuous Monitoring and Intervention11. Emergency Response Systems Powered by Predictive Digital Twins12. Integration with EHR and Smart Hospital Systems13. Ethical AI in Healthcare Twins: Privacy, Regulation, and Fairness14. Evaluation and Validation Metrics for Healthcare Digital Twins15. Interoperability Standards and Open Frameworks for Digital Health Ecosystems16. Global Case Studies: Twin Deployments Across HealthTech Ecosystems17. Future Horizons 4.0: Cognitive Twins, Federated Intelligence, and Quantum Simulation18. Healthcare Workforce Readiness and Training19. Eco-Sustainability and Green Computing in Smart Healthcare20. Legal and Regulatory Compliance in Digital Twin-Enabled Healthcare
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