Innovation in Health Informatics: Driving Value-Based Healthcare through Economic Efficiency, Second Edition addresses rapid advancements in health informatics by integrating the latest technologies and methodologies. The revised edition includes new chapters on Digital Twins, Blockchain, AI Applications for Personalized Medicine, and Health Analytics Dashboards, enriching foundational topics. The book delves into the economic implications and practical applications of these technologies, offering evidence-based strategies for their integration into healthcare systems. For the academic audience, this book bridges the gap between theory and practice, featuring practical case studies, end-of-chapter summaries, and interactive components like QR codes linking to online resources and simulation videos.
The primary goals of this revision are to update the book with the latest technological advancements, expand the scope to include emerging topics, and enhance existing chapters, ensuring it remains a comprehensive resource for professionals and students. This updated edition equips readers with up-to-date knowledge and tools to navigate and innovate within the evolving landscape of health informatics.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xxi 7. Preface - p. xxiii 8. Acknowledgements - p. xxvii 9. Section I: Smart healthcare in the era of big data and data science - p. S1 10. Chapter 1. Artificial intelligence-driven health informatics: Setting the new landscape for personalized and value-based healthcare - p. 3 11. Chapter 2. Smart healthcare: Emerging technologies, best practices and sustainable policies - p. 39 12. Chapter 3. Syndromic surveillance using web data: A systematic review - p. 89 13. Chapter 4. Digital twin technology: Foundations, applications and implications for next generation healthcare - p. 127 14. Chapter 5. Natural language processing, sentiment analysis and clinical analytics: From traditional approaches to large language models - p. 145 15. Section II: Advanced decision making and artificial intelligence for smart healthcare - p. S169 16. Chapter 6. Clinical decision support for infection control in surgical care - p. 171 17. Chapter 7. Human activity recognition using artificial intelligence and machine learning in Internet of Things–enabled healthcare systems - p. 193 18. Chapter 8. Application of machine learning and image processing for detection of breast cancer - p. 217 19. Chapter 9. Preserving critical health information: Challenges and innovations in healthcare systems - p. 237 20. Section III: Emerging technologies and systems for smart healthcare - p. S261 21. Chapter 10. The foundations of artificial intelligence: Towards new models of healthcare delivery and innovative services - p. 263 22. Chapter 11. Security and privacy solutions for smart healthcare systems - p. 287 23. Chapter 12. Cloud-based health monitoring framework using smart sensors and smartphone - p. 315 24. Chapter 13. Artificial intelligence–assisted detection of diabetic retinopathy on digital fundus images: Concepts and applications in the National Health Service - p. 343 25. Chapter 14. The next generation of medical applications based on virtual reality and sensors - p. 363 26. Chapter 15. A smart portable diagnostic solution for early-stage detection of diabetic retinopathy - p. 387 27. Chapter 16. Improved nodule detection in chest X-rays using principal component analysis filters - p. 405 28. Chapter 17. The Internet of Medical Things and personal area networks: Standards, challenges, and applications in smart healthcare - p. 435 29. Section IV: Social issues and policy making for smart healthcare - p. S455 30. Chapter 18. Threats to patients’ privacy in smart healthcare environment: From traditional vulnerabilities to blockchain and quantum-era challenges - p. 457 31. Chapter 19. Policy implications for smart healthcare: The international collaboration dimension - p. 481 32. Chapter 20. Health Informatics 2040: A robust and sustainable pathway to super intelligence - p. 495 33. Author Index - p. 517 34. Index - p. 527
Innovation in Health Informatics: Driving Value-Based Healthcare through Economic Efficiency, Second Edition addresses rapid advancements in health informatics by integrating the latest technologies and methodologies. The revised edition includes new chapters on Digital Twins, Blockchain, AI Applications for Personalized Medicine, and Health Analytics Dashboards, enriching foundational topics. The book delves into the economic implications and practical applications of these technologies, offering evidence-based strategies for their integration into healthcare systems. For the academic audience, this book bridges the gap between theory and practice, featuring practical case studies, end-of-chapter summaries, and interactive components like QR codes linking to online resources and simulation videos.
The primary goals of this revision are to update the book with the latest technological advancements, expand the scope to include emerging topics, and enhance existing chapters, ensuring it remains a comprehensive resource for professionals and students. This updated edition equips readers with up-to-date knowledge and tools to navigate and innovate within the evolving landscape of health informatics.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xxi 7. Preface - p. xxiii 8. Acknowledgements - p. xxvii 9. Section I: Smart healthcare in the era of big data and data science - p. S1 10. Chapter 1. Artificial intelligence-driven health informatics: Setting the new landscape for personalized and value-based healthcare - p. 3 11. Chapter 2. Smart healthcare: Emerging technologies, best practices and sustainable policies - p. 39 12. Chapter 3. Syndromic surveillance using web data: A systematic review - p. 89 13. Chapter 4. Digital twin technology: Foundations, applications and implications for next generation healthcare - p. 127 14. Chapter 5. Natural language processing, sentiment analysis and clinical analytics: From traditional approaches to large language models - p. 145 15. Section II: Advanced decision making and artificial intelligence for smart healthcare - p. S169 16. Chapter 6. Clinical decision support for infection control in surgical care - p. 171 17. Chapter 7. Human activity recognition using artificial intelligence and machine learning in Internet of Things–enabled healthcare systems - p. 193 18. Chapter 8. Application of machine learning and image processing for detection of breast cancer - p. 217 19. Chapter 9. Preserving critical health information: Challenges and innovations in healthcare systems - p. 237 20. Section III: Emerging technologies and systems for smart healthcare - p. S261 21. Chapter 10. The foundations of artificial intelligence: Towards new models of healthcare delivery and innovative services - p. 263 22. Chapter 11. Security and privacy solutions for smart healthcare systems - p. 287 23. Chapter 12. Cloud-based health monitoring framework using smart sensors and smartphone - p. 315 24. Chapter 13. Artificial intelligence–assisted detection of diabetic retinopathy on digital fundus images: Concepts and applications in the National Health Service - p. 343 25. Chapter 14. The next generation of medical applications based on virtual reality and sensors - p. 363 26. Chapter 15. A smart portable diagnostic solution for early-stage detection of diabetic retinopathy - p. 387 27. Chapter 16. Improved nodule detection in chest X-rays using principal component analysis filters - p. 405 28. Chapter 17. The Internet of Medical Things and personal area networks: Standards, challenges, and applications in smart healthcare - p. 435 29. Section IV: Social issues and policy making for smart healthcare - p. S455 30. Chapter 18. Threats to patients’ privacy in smart healthcare environment: From traditional vulnerabilities to blockchain and quantum-era challenges - p. 457 31. Chapter 19. Policy implications for smart healthcare: The international collaboration dimension - p. 481 32. Chapter 20. Health Informatics 2040: A robust and sustainable pathway to super intelligence - p. 495 33. Author Index - p. 517 34. Index - p. 527
