Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare

by Adam Bohr, Kaveh Memarzadeh
Released June 2020
Publisher(s): Academic Press
ISBN: 9780128184394

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Book description

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare.

  • Highlights different data techniques in healthcare data analysis, including machine learning and data mining
  • Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks
  • Includes applications and case studies across all areas of AI in healthcare data

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Endorsement
  6. List of contributors
  7. About the editors
  8. Biographies
  9. Preface
    1. About this book
    2. Intended audience
    3. How is this book organized
  10. Introduction
    1. The promise of an intelligent machine
    2. Current applications and challenges in healthcare
  11. Chapter 1. Current healthcare, big data, and machine learning
    1. Abstract
    2. 1.1 Current healthcare practice
    3. 1.2 Value-based treatments and healthcare services
    4. 1.3 Increasing data volumes in healthcare
    5. 1.4 Analytics of healthcare data (machine learning and deep learning)
    6. 1.5 Conclusions/summary
    7. References
  12. Chapter 2. The rise of artificial intelligence in healthcare applications
    1. Abstract
    2. 2.1 The new age of healthcare
    3. 2.2 Precision medicine
    4. 2.3 Artificial intelligence and medical visualization
    5. 2.4 Intelligent personal health records
    6. 2.5 Robotics and artificial intelligence-powered devices
    7. 2.6 Ambient assisted living
    8. 2.7 The artificial intelligence can see you now
    9. References
  13. Chapter 3. Drug discovery and molecular modeling using artificial intelligence
    1. Abstract
    2. 3.1 Introduction. The scope of artificial intelligence in drug discovery
    3. 3.2 Various types of machine learning in artificial intelligence
    4. 3.3 Molecular modeling and databases in artificial intelligence for drug molecules
    5. 3.4 Computational mechanics ML methods in molecular modeling
    6. 3.5 Drug characterization using isopotential surfaces
    7. 3.6 Drug design for neuroreceptors using artificial neural network techniques
    8. 3.7 Specific use of deep learning in drug design
    9. 3.8 Possible future artificial intelligence development in drug design and development
    10. References
  14. Chapter 4. Applications of artificial intelligence in drug delivery and pharmaceutical development
    1. Abstract
    2. 4.1 The evolving pharmaceutical field
    3. 4.2 Drug delivery and nanotechnology
    4. 4.3 Quality-by-design R&D
    5. 4.4 Artificial intelligence in drug delivery modeling
    6. 4.5 Artificial intelligence application in pharmaceutical product R&D
    7. 4.6 Landscape of AI implementation in the drug delivery industry
    8. 4.7 Conclusion: the way forward
    9. References
  15. Chapter 5. Cancer diagnostics and treatment decisions using artificial intelligence
    1. Abstract
    2. 5.1 Background
    3. 5.2 Artificial intelligence, machine learning, and deep learning in cancer
    4. 5.3 Artificial intelligence to determine cancer susceptibility
    5. 5.4 Artificial intelligence for enhanced cancer diagnosis and staging
    6. 5.5 Artificial intelligence to predict cancer treatment response
    7. 5.6 Artificial intelligence to predict cancer recurrence and survival
    8. 5.7 Artificial intelligence for personalized cancer pharmacotherapy
    9. 5.8 How will artificial intelligence affect ethical practices and patients?
    10. 5.9 Concluding remarks
    11. References
  16. Chapter 6. Artificial intelligence for medical imaging
    1. Abstract
    2. 6.1 Introduction
    3. 6.2 Outputs of artificial intelligence in radiology/medical imaging
    4. 6.3 Using artificial intelligence in radiology and overcoming its hurdles
    5. 6.4 X-rays and artificial intelligence in medical imaging—case 1 (Zebra medical vision)
    6. 6.5 Ultrasound and artificial intelligence in medical imaging—case 2 (Butterfly iQ)
    7. 6.6 Application of artificial intelligence in medical imaging—case 3 (Arterys)
    8. 6.7 Perspectives
    9. References
  17. Chapter 7. Medical devices and artificial intelligence
    1. Abstract
    2. 7.1 Introduction
    3. 7.2 The development of artificial intelligence in medical devices
    4. 7.3 Limitations of artificial intelligence in medical devices
    5. 7.4 The future frontiers of artificial intelligence in medical devices
    6. References
  18. Chapter 8. Artificial intelligence assisted surgery
    1. Abstract
    2. 8.1 Introduction
    3. 8.2 Preoperative
    4. 8.3 Intraoperative
    5. 8.4 Postoperative
    6. 8.5 Conclusion
    7. References
    8. Further reading
  19. Chapter 9. Remote patient monitoring using artificial intelligence
    1. Abstract
    2. 9.1 Introduction to remote patient monitoring
    3. 9.2 Deploying patient monitoring
    4. 9.3 The role of artificial intelligence in remote patient monitoring
    5. 9.4 Diabetes prediction and monitoring using artificial intelligence
    6. 9.5 Cardiac monitoring using artificial intelligence
    7. 9.6 Neural applications of artificial intelligence and remote patient monitoring
    8. 9.7 Conclusions
    9. References
  20. Chapter 10. Security, privacy, and information-sharing aspects of healthcare artificial intelligence
    1. Abstract
    2. 10.1 Introduction to digital security and privacy
    3. 10.2 Security and privacy concerns in healthcare artificial intelligence
    4. 10.3 Artificial intelligence’s risks and opportunities for data privacy
    5. 10.4 Addressing threats to health systems and data in the artificial intelligence age
    6. 10.5 Defining optimal responses to security, privacy, and information-sharing challenges in healthcare artificial intelligence
    7. 10.6 Conclusions
    8. Acknowledgements
    9. References
  21. Chapter 11. The impact of artificial intelligence on healthcare insurances
    1. Abstract
    2. 11.1 Overview of the global health insurance industry
    3. 11.2 Key challenges facing the health insurance industry
    4. 11.3 The application of artificial intelligence in the health insurance industry
    5. 11.4 Case studies
    6. 11.5 Moral, ethical, and regulatory concerns regarding the use of artificial intelligence
    7. 11.6 The limitations of artificial intelligence
    8. 11.7 The future of artificial intelligence in the health insurance industry
    9. References
  22. Chapter 12. Ethical and legal challenges of artificial intelligence-driven healthcare
    1. Abstract
    2. 12.1 Understanding “artificial intelligence”
    3. 12.2 Trends and strategies
    4. 12.3 Ethical challenges
    5. 12.4 Legal challenges
    6. 12.5 Conclusion
    7. Acknowledgements
    8. References
  23. Concluding remarks
  24. Index

Product information

  • Title: Artificial Intelligence in Healthcare
  • Author(s): Adam Bohr, Kaveh Memarzadeh
  • Release date: June 2020
  • Publisher(s): Academic Press
  • ISBN: 9780128184394