Main description:

This book discusses the applications and optimization of emerging smart technologies in the field of healthcare. It further explains different modeling scenarios of the latest technologies in the healthcare system and compares the results to better understand the nature and progress of diseases in the human body, which would ultimately lead to early diagnosis and better treatment and cure of diseases with the help of distributed technology.

Covers the implementation models using technologies such as artificial intelligence, machine learning, and deep learning with distributed systems for better diagnosis and treatment of diseases.

Gives in-depth review of technological advancements like advanced sensing technologies such as plasmonic sensors, usage of RFIDs, and electronic diagnostic tools in the field of healthcare engineering.

Discusses possibilities of augmented reality and virtual reality interventions for providing unique solutions in medical science, clinical research, psychology, and neurological disorders.

Highlights the future challenges and risks involved in the application of smart technologies such as cloud computing, fog computing, IOT, and distributed computing in healthcare.

Confers to utilize the AI and ML and associated aids in healthcare sectors in the post-Covid 19 period to revitalize the medical setup.

Contributions included in the book will motivate technological developers and researchers to develop new algorithms and protocols in the healthcare field. It will serve as a vast platform for gaining knowledge regarding healthcare delivery, health- care management, healthcare in governance, and health monitoring approaches using distributed environments. It will serve as an ideal reference text for graduate students and researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical fields.

Contents:

Chapter 1: Healthcare Engineering Using AI and Distributed Technologies
1.1 Introduction:
1.2 Related work
1.3 Impact of AI in the healthcare industry
1.4 Transforming healthcare with distributed computing
1.5 AI-based Robots in the healthcare ecosystem
1.6 Conclusion and Future Scope

Chapter 2: Cloud Computing in Healthcare: A Systematic Study
2.1. Introduction
2.2. Literature Review
2.3. MEDLINE
2.4 Monitoring Software for the Cloud
2.5 Biomedicine and healthcare benefit from cloud computing
2.6 Biotech Solutions in the Cloud
2.7. Cloud-based Molecular Simulation Tools
2.8 Cloud-based Medical Imaging Solutions
2.9. Medical Solutions in the Cloud
2.10. Fog computing and healthcare
2.11. Threats with cloud computing
2.12. Future Research
2.13 Conclusion

Chapter 3: Medical Information Extraction of Clinical Notes and Pictorial Visualization of Electronic Medical Records Summary Interface

3.1 INTRODUCTION
3.2 RELATED WORKS
3.3 PICTORIAL VISUALIZATION OF DATA
3.4 METHODOLOGY FOR INFORMATION EXTRACTION
3.5 RESULTS
3.6 CONCLUSION AND FUTURE WORK

Chapter 4: Investigations on RFID Enabled Healthcare Usage and Adoption Issues
4.1 Abstract
4.2 Background
4.3 RFID in Health Care System
4.4 RFID Adoption Issues
4.5 Conclusion
References

Chapter 5: Photonic crystal fiber plasmonic sensor for applications in medicine
5.1 Introduction
5.2 Background and development of photonic crystal fiber
5.3 Plasmonic sensor based on photonic crystal fiber
5.4 Fabrication Techniques
5.5 Future applications of plasmonic sensors
5.6 Conclusion

Chapter 6: (Augmented reality as a boon to disability)
6.1 Introduction: Aim and real use cases of augmented reality
6.2 Related work And Discussion
6.3 Technology Advancement Using AR for Empowering Disabled People
6.4 AR solutions for teaching specialized students
6.5 AR accessible technology to people
6.6 Conclusion

Chapter 7: (Augmented and Virtual Reality: Transforming the Future of Psychological and Medical Sciences)
7.1. Introduction
7.2 Use of AR Technology in Medical Science
7.3 Challenges and Opportunities
7.4 Conclusion

Chapter 8: Artificial Intelligence in Healthcare: Perspectives from Post-Pandemic times
8.2 Introduction
8.3 Applications of artificial intelligence (AI) in healthcare before Covid-19 pandemic
8.4 An Account of artificial intelligence (AI) guided aids in healthcare: Scenario from post pandemic times
8.5 Discussion
8.6 Conclusion

Chapter 9: Bioweapons v/s Computer Based Counter Measure Techniques and Mathematical modeling for prediction of Covid-19
9.1 Introduction and history
9.2 Genetically Engineered pathogens
9.3 Counter measure by computer based techniques
9.4 Mathematical model for COVID-19 Prediction
9.5 Conclusion

Chapter 10: Evolution of Healthcare Sector and Evolving Cyber Attacks - A Summary
10.1 Healthcare industry and its revolution:
10.2 Role of Distributed System in Health Care
10.3 Why Healthcare is the biggest target for cyber attackers?
10.4 Cyber-attacks in healthcare industries - an infographic
10.5 Most frequent attacks in health industries and remedial measures
10.6 Research trends in cybersecurity for the health care sector
10.7 Conclusion - Defending Healthcare sector from Cyberattacks

Chapter 11: Improving Cardiovascular Health by Deep learning
11.1 Introduction
11.2. Machine Learning
11.3 Next Generation Machine Learning
11.4 Applications of Artificial Intelligence for Cardiovascular Health
11.5 Future Scope
11.6 Challenges
11.7 Conclusion