Smart Healthcare 2.0 : Integrating Digital Twins with Ai-Driven Predictive Analytics
Language: English
Published by Elsevier Science Sep 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Neuware - 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.…
Seller Inventory # 9780443452826
- Title
- Smart Healthcare 2.0 : Integrating Digital Twins with Ai-Driven Predictive Analytics
- Author
- Kamal Upreti
- Publisher
- Elsevier Science Sep 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0443452822
- ISBN 13
- 9780443452826
- Item weight
- 925 grams
- Dimensions
- 236x193x22 mm
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
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Kamal Upreti is an Associate Professor of Computer Science at CHRIST (Deemed to be University), Ghaziabad. He holds , a Ph.D. in Computer Science & Engineering, and a postdoctoral fellowship at National Taipei University of Business, Taiwan, funded by MHRD.
With teaching, research, and industry exposure, he has produced numerous patents and publications. His interests span modern physics, data analytics, cybersecurity, ML, healthcare, embedded systems, and cloud computing. Notable projects include Hydrastore in Japan, IPDS in India, and an ICMR-funded cardiovascular-prediction project with GB Pant and AIIMS Delhi.
Dr. Upreti serves as session chair, keynote speaker, trainer, and faculty developer, and has been honored as Best Teacher, Best Researcher, and an M.Tech Gold Medalist.
"About the title" may belong to another edition of this title.
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