Digital Twin Technologies for Healthcare 4.0 /

In healthcare, a digital twin is a digital representation of a patient or healthcare system using integrated simulations and service data. The digital twin tracks a patient's records, crosschecks them against registered patterns and analyses any diseases or contra indications. The digital twin...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Dhanaraj, Rajesh Kumar (Editor ), Murugesan, Santhiya (Editor ), Balusamy, Balamurugan (Editor ), Balas, Valentina Emilia (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hertfordshire, United Kingdom : Institution of Engineering & Technology, 2022.
Colección:Healthcare technologies series ; 46.
Temas:
Medicine > Computer simulation.
Digital twins (Computer simulation)
Medical innovations.
Medical Informatics
Médecine > Simulation par ordinateur.
Médecine > Innovations.
Médecine > Informatique.
Medical innovations
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Title
  • Copyright
  • Contents
  • About the editors
  • 1 Introduction: digital twin technology in healthcare
  • 1.1 Introduction
  • 1.2 Digital twin
  • background study
  • 1.3 Research on digital twin technologies
  • 1.4 Digital twin sectors in healthcare
  • 1.4.1 Digital patient
  • 1.4.2 Pharmaceutical industry
  • 1.4.3 Hospital
  • 1.4.4 Wearable technologies
  • 1.5 Challenges and issues in implementation
  • 1.5.1 Trust
  • 1.5.2 Security and privacy
  • 1.5.3 Standardization
  • 1.5.4 Diversity and multisource
  • References
  • 2 Convergence of Digital Twin, AI, IOT, and machine learning techniques for medical diagnostics
  • 2.1 Introduction
  • 2.2 DT technology
  • 2.2.1 Steps in DT creation
  • 2.2.2 DT types and functions
  • 2.3 DT and its supporting technologies
  • AI, Cloud computing, DL, Big Data analytics, ML, and IoT
  • 2.4 DT integration with other technologies for medical diagnosis and health management
  • 2.5 DT technology and its application
  • 2.5.1 DT application in manufacturing industry
  • 2.5.2 Applications of DT in automotive & aerospace
  • 2.5.3 Medicine diagnosis and device development
  • 2.5.4 Wind twin technology
  • 2.6 Conclusion
  • References
  • 3 Application of digital twin technology in model-based systems engineering
  • 3.1 Evolution of DTT
  • 3.2 Basic concepts of DTT
  • 3.3 DTT implementation in power system
  • 3.3.1 Characteristics of DTT in power systems
  • 3.4 Power system network modeling using DTT
  • 3.4.1 Model-based approach
  • 3.4.2 Data-driven approach
  • 3.4.3 Combination of both
  • 3.5 Integration of power system with DTT
  • 3.6 Future scope of DTT in power systems
  • 3.7 Conclusion
  • References
  • 4 Digital twins in e-health: adoption of technology and challenges in the management of clinical systems
  • 4.1 Introduction
  • 4.2 Digital twin
  • 4.3 Evolution of healthcare services
  • 4.4 Elderly medical services and demands
  • 4.5 Cloud computing
  • 4.6 Cloud computing DT in healthcare
  • 4.6.1 Use cases
  • 4.7 Digital healthcare modeling process
  • 4.8 Cloud-based healthcare facility platform
  • 4.9 Applications of DT technology
  • 4.9.1 Cardiovascular application
  • 4.9.2 Cadaver high temperature
  • 4.9.3 Diabetes meters
  • 4.9.4 Stress monitoring
  • 4.10 Benefits of DT technology
  • 4.10.1 Remote monitoring
  • 4.10.2 Group cooperation
  • 4.10.3 Analytical maintenance
  • 4.10.4 Transparency
  • 4.10.5 Future prediction
  • 4.10.6 Information
  • 4.10.7 Big data analytics and processing
  • 4.10.8 Cost effectiveness
  • 4.11 DT challenges in healthcare
  • 4.11.1 Cost effectiveness
  • 4.11.2 Data collection
  • 4.11.3 Data protection
  • 4.11.4 Team collaboration
  • 4.11.5 Monitoring
  • 4.11.6 Software maintenance and assurance
  • 4.11.7 Regulatory complications
  • 4.11.8 Security and privacy-related issues
  • 4.11.9 Targets of attackers
  • 4.12 Conclusion
  • References

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