Revolutionizing Digital Healthcare Through Artificial Intelligence and Automation : Principles, Technologies, and Applications.

Format:

Book

Author/Creator:

Khang, Alex.

Language:

English

Subjects (All):

Artificial intelligence.

Medical technology.

Physical Description:

1 online resource (797 pages)

Edition:

1st ed.

Place of Publication:

Chantilly : Elsevier Science & Technology, 2025.

Summary:

Revolutionizing Digital Healthcare Through Artificial Intelligence and Automation: Principles, Technologies, and Applications is a transformative exploration of how Artificial Intelligence (AI) and automation technologies are reshaping the healthcare landscape.

Contents:

Front Cover

Front Matter

Titlepage

Copyright

Contents

Contributors

Preface

Acknowledgments

Chapter 1 Principles and models of digital healthcare ecosystem

1.1 Introduction

1.2 Methodology

1.3 Literature review

1.3.1 Patient-centricity

1.3.2 Interoperability

1.3.3 Data-driven decision making

1.3.4 Accessibility and equity

1.4 Research ideas in digital healthcare

1.5 Experiments in digital healthcare

1.5.1 Telemedicine effectiveness

1.5.2 Mobile health application impact

1.6 Results

1.6.1 Mobile health application study

1.6.2 Density plot

1.7 Discussion

1.8 Case studies

1.8.1 Case study 1: Remote patient monitoring

1.8.2 Case study 2: Digital mental health services

1.8.3 Case study 3: Telehealth for chronic disease management

1.8.4 Case study 4: Mobile health application for asthma management

1.8.5 Case study 5: AI-driven predictive analytics in hospital settings

1.9 Real-world examples

1.9.1 Telehealth initiatives during COVID-19

1.9.2 Wearable technology in health management

1.10 Conclusion

References

Chapter 2 The role of Artificial Intelligence (AI) and Generative Artificial Intelligence (Gen AI) in digital healthcare

2.1 Introduction

2.2 Artificial intelligence in healthcare

2.2.1 Significance of artificial intelligence in healthcare

2.2.2 How artificial intelligence works in healthcare

2.2.3 Applications of artificial intelligence in healthcare

2.3 Generative artificial intelligence in healthcare

2.3.1 Generative pretrained transformers

2.3.2 Generative adversarial networks

2.4 Comparison between generative pretrained transformer and generative adversarial networks models

2.5 Case studies

2.5.1 Operationalizing generative pretrained transformer-3 in healthcare.

2.5.2 Artificial intelligence-driven chatbots in urology

2.5.3 Accelerating drug discovery with artificial intelligence

2.6 Challenges of artificial intelligence and generative artificial intelligence in healthcare

2.6.1 Ethical and legal challenges

2.6.2 Technical challenges

2.7 Future trends and innovations

2.7.1 Quantum computing with artificial intelligence in healthcare

2.7.2 6G networks and healthcare artificial intelligence

2.7.3 Untapped areas of artificial intelligence in healthcare

2.8 Conclusion

Chapter 3 An extensive analysis of artificial intelligence and internet of things for modern healthcare realm

3.1 Introduction

3.2 Distant carers

3.3 Healthcare internet of things systems

3.3.1 Generic internet of things characteristic features

3.3.2 Healthcare internet of things characteristic features

3.4 Architecture and framework of healthcare internet of things systems

3.5 Machine learning in healthcare internet of things systems

3.6 Blockchain in healthcare internet of things systems

3.7 Conclusion

Chapter 4 Applications of artificial intelligence and generative artificial intelligence in digital healthcare ecosystem

4.1 Introduction

4.1.1 Overview of digital healthcare

4.1.2 Role of artificial intelligence in healthcare

4.1.3 Emergence of generative artificial intelligence

4.2 Artificial intelligence in digital healthcare

4.3 Generative artificial intelligence in digital healthcare

4.3.1 Generative artificial intelligence in electronic health record

4.3.2 Simplifying medical language

4.3.3 Wearable internet of things and sensor networks

4.3.4 Personalized healthcare

4.4 Artificial intelligence in discovering new drugs

4.4.1 Historical background

4.4.2 Virtual health assistant.

4.5 Ethical considerations and challenges

4.6 Future trends and opportunities

4.6.1 Artificial intelligence integration with other technologies

4.6.2 Generative artificial intelligence for complex simulation real-life applications

4.6.3 AI in global health

4.7 Conclusion

Chapter 5 Advancements and applications in the smart healthcare ecosystem

5.1 Introduction

5.1.1 Definition and significance of the digital healthcare ecosystem

5.1.2 Evolution and current state of smart health care

5.1.3 Objectives and organization of the chapter

5.2 Principles and models of the digital healthcare ecosystem

5.2.1 Core principles of digital health care

5.2.2 Models and frameworks for digital healthcare delivery

5.3 Role of artificial intelligence and generative artificial intelligence in the digital healthcare ecosystem

5.3.1 Overview of artificial intelligence and generative artificial intelligence technologies

5.3.2 Integration of artificial intelligence in healthcare systems

5.3.3 Benefits and challenges of artificial intelligence in health care

5.4 Cutting-edge technologies in the digital healthcare ecosystem

5.4.1 Overview of emerging technologies

5.4.2 Comparative analysis of various technologies

5.4.3 Impact on healthcare delivery and patient outcomes

5.5 Application of artificial intelligence and generative artificial intelligence in the digital healthcare ecosystem

5.5.1 Diagnostic applications

5.5.2 Treatment planning and personalized medicine

5.5.3 Predictive analytics and patient monitoring

5.6 Embedded artificial intelligence-based applications for smart healthcare systems

5.6.1 Definition and significance of embedded artificial intelligence

5.6.2 Key applications and use cases

5.6.3 Technical challenges and solutions.

5.7 Internet-of-things-based technologies for smart healthcare systems

5.7.1 Role of internet of things in health care

5.7.2 Key internet-of-things applications and devices

5.7.3 Benefits and security concerns

5.8 Artificial intelligence-based robotics for smart healthcare systems

5.8.1 Overview of robotics in health care

5.8.2 Future prospects and ethical considerations

5.9 Sensor technologies and applications for smart healthcare systems

5.9.1 Types of sensors used in health care

5.9.2 Key applications in patient monitoring and diagnostics

5.9.3 Integration with other technologies and systems

5.10 Cybersecurity and cloud platforms for smart healthcare systems

5.10.1 Importance of cybersecurity in health care

5.10.2 Role of cloud platforms in smart health care

5.10.3 Strategies for ensuring data security and privacy

5.11 Future prospects and challenges for smart healthcare systems

5.11.1 Emerging trends and future prospects

5.11.2 Key challenges and potential solutions

5.11.3 Roadmap for future research and development

5.12 Conclusion

Chapter 6 Enhancing healthcare services with artificial intelligence and generative artificial intelligence technologies

6.1 Introduction

6.1.1 Background and motivation

6.1.2 Scope and objectives

6.2 Overview of artificial intelligence and generative artificial intelligence in healthcare

6.2.1 Definition

6.2.2 Historical development and milestones

6.2.3 Types of artificial intelligence technologies in health care

6.3 Applications of artificial intelligence and generative artificial intelligence in healthcare

6.4 Case studies

6.4.1 Successful implementations

6.4.2 Lessons learned and best practices

6.5 Ethical considerations and challenges

6.5.1 Data privacy and security.

6.5.2 Bias and fairness in artificial intelligence algorithms

6.5.3 Regulatory and legal issues

6.5.4 Patient acceptance and trust

6.6 Impact on healthcare outcomes

6.6.1 Improving diagnostic accuracy

6.6.2 Enhancing treatment effectiveness

6.6.3 Operational benefits and cost savings

6.6.4 Patient experience and engagement

6.7 Future prospects and research directions

6.7.1 Emerging trends in artificial intelligence and generative artificial intelligence technologies

6.7.2 Potential impact on healthcare delivery

6.7.3 Recommendations for future research

6.8 Conclusion

Chapter 7 Integrating artificial intelligence and internet of things for smart healthcare systems

7.1 Introduction

7.2 Enhancing patient care through internet of things-enabled healthcare solutions

7.2.1 Smart health monitoring

7.2.2 Case studies

7.3 Revolutionizing healthcare

7.3.1 The role of internet of things in advancing telemedicine

7.3.2 Interoperability and device standardization in internet of things for telemedicine

7.4 Challenges and limitations in implementing internet of things in telemedicine

7.4.1 Advantages of a unified patient record system

7.4.2 Enhancing internet of things-driven healthcare systems with machine learning: A synergistic approach

7.5 Machine learning in analyzing electronic health records

7.5.1 Challenges in adopting machine learning in electronic health records

7.5.2 Clinical decision support system

7.6 Personalized care using artificial intelligence

7.7 Robotics in healthcare using internet of things

7.7.1 Surgical robots

7.7.2 Patient monitoring robots using internet of things

7.7.3 Nanobots

7.8 Challenges and factors in implementing robotics in healthcare

7.9 Hospital management systems.

7.9.1 Key functionalities of a hospital management systems.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

0-443-36435-4

9780443364358

OCLC:

1547901481