Digital Health Transformation With Blockchain and Artificial Intelligence

Length: 321 pages
Edition: 1
Language: English
Publisher: CRC Pr I Llc
Publication Date: 2022-05-11
ISBN-10: 1032161183
ISBN-13: 9781032161181
Sales Rank: #0 (See Top 100 Books)

The book Digital Health Transformation with Blockchain and Artificial Intelligence covers the global digital revolution in the field of healthcare sector. The population has been overcoming the COVID-19 period; therefore, we need to establish intelligent digital healthcare systems using various emerging technologies like Blockchain and Artificial Intelligence. Internet of Medical Things is the technological revolution that has included the element of smartness in the healthcare industry and also identifying, monitoring, and informing service providers about the patient’s clinical information with faster delivery of care services. This book highlights the important issues i.e. (a) How Internet of things can be integrated with the healthcare ecosystem for better diagnostics, monitoring, and treatment of the patients, (b) Artificial Intelligence for predictive and preventive healthcare systems, (c) Blockchain for managing healthcare data to provide transparency, security, and distributed storage, and (d) Effective remote diagnostics and telemedicine approach for developing smart care. The book encompasses chapters belong to the blockchain, Artificial Intelligence, and Big health data technologies.

Features:

Blockchain and internet of things in healthcare systems
Secure Digital Health Data Management in Internet of Things
Public Perception towards AI-Driven Healthcare
Security, privacy issues and challenges in adoption of smart digital healthcare
Big data analytics and Internet of things in the pandemic era
Clinical challenges for digital health revolution
Artificial intelligence for advanced healthcare
Future Trajectory of Healthcare with Artificial Intelligence 9
Parkinson disease pre-diagnosis using smart technologies
Emerging technologies to combat the COVID-19
Machine Learning and Internet of Things in Digital Health Transformation
Effective Remote Healthcare and Telemedicine Approaches

Legal implication of blockchain technology in public health This Book on Digital Health Transformation with Blockchain and Artificial Intelligence aims at promoting and facilitating exchanges of research knowledge and findings across different disciplines on the design and investigation of secured healthcare data analytics. It can also be used as a textbook for a Masters course in security and biomedical engineering. This book will also present new methods for the medical data analytics, blockchain technology, and diagnosis of different diseases to improve the quality of life in general, and better integration into digital healthcare.

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Book Organization
About the Editor
Contributors
Chapter 1: Blockchain and Internet of Things in Healthcare Systems: Prospects, Issues, and Challenges
	1.1 Introduction
	1.2 Literature Review
	1.3 Blockchain Technology and IoT
		1.3.1 Features of Blockchain
		1.3.2 The Internet of Things
		1.3.3 Blockchain and IoT Technologies Integration in Healthcare
		1.3.4 Digital Health Transformation Using AI
	1.4 Challenges and Prospects of Using Blockchain and IoT in Healthcare
	1.5 Proposed Framework
	1.6 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 2: Secure Digital Health Data Management in Internet of Things Using Blockchain and Machine Learning
	2.1 Introduction
	2.2 Background and Related Work
	2.3 Proposed Model
	2.4 Methodology
	2.5 Implementation and Data Analysis
	2.6 Conclusion
	2.7 Future Research Directions
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 3: Revolutionizing Healthcare by Coupling Unmanned Aerial Vehicles (UAVs) to Internet of Medical Things (IoMT)
	3.1 Introduction
	3.2 Wireless Communication Systems: A UAV Case
	3.3 Revolutionizing Smart Healthcare
		3.3.1 Rationale of Considering IoMT
			3.3.1.1 Wellbeing and Early Detection
			3.3.1.2 Patient Support
			3.3.1.3 Improving Professional Medical Services
			3.3.1.4 Data Analytics
		3.3.2 IoMT Overview and Architecture
		3.3.3 IoMT Wide Application
	3.4 Trends and Smart Healthcare of IoMT-Enabled UAVs
	3.5 Conclusion
	References
Chapter 4: Public Perception toward AI-Driven Healthcare and the Way Forward in the Post-Pandemic Era
	4.1 Introduction
	4.2 Literature Review
		4.2.1 Research Gap
			4.2.1.1 Research Variables
		4.2.2 Research Objectives
		4.2.3 Methodology
			4.2.3.1 Sampling
		4.2.4 Data Analysis
	4.3 Discussion
	4.4 Conclusion
	4.5 Future Scope
	References
Chapter 5: Security, Privacy Issues, and Challenges in Adoption of Smart Digital Healthcare
	5.1 Introduction
		5.1.1 Smart Healthcare System Associate Technologies
		5.1.2 Smart Healthcare Planning: Essentials, Elements and Features
		5.1.3 IoT Enables Smart Healthcare System
	5.2 Literature Survey
	5.3 Security and Privacy Challenges in Smart Healthcare
	5.4 Problem Statement
	5.5 Proposed Methodology
	5.6 Implementation
		5.6.1 Recommendations for the Development of Smart Contract and Their Cooperation with Smart Medical System
	5.7 Conclusion
	References
Chapter 6: Tapping the Big Data Analytics and IoT in the Pandemic Era
	6.1 Introduction
	6.2 Connecting Big Data and IoT to Digital Health
		6.2.1 The Big Data Analytics BDA Support
		6.2.2 IoT Support: Sensing Systems That Collect Data
	6.3 Building Resilience using Big Data Analytics and IoT in Pandemic Conditions
	6.4 Fighting Pandemic using Big Data Analytics
	6.5 Collecting Big Data Analytics in Healthcare during a Pandemic
	6.6 Exploratory Study
		6.6.1 Introduction
		6.6.2 Applications of Artificial Intelligence and Machine Learning in the Medical Sector
		6.6.3 Implications of AI and ML in Social and Information Science
		6.6.4 The Possible Uses of IoT
		6.6.5 The Risks that can arise while using these Intelligent Equipment and Techniques
	6.7 Drive through the Future: IoT to IoMT
		6.7.1 Medical IoT
		6.7.2 IoT to Dissect an Outbreak
		6.7.3 Protocols for Preventive Containment
		6.7.4 Upgrades in Connectivity Eternity
		6.7.5 Consultations in M-health
		6.7.6 The Advent of the Robotics
	6.8 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 7: The Clinical Challenges for Digital Health Revolution
	7.1 Introduction
	7.2 History of Digital Health
	7.3 Digital Health and the Healthcare Professionals
	7.4 Digital Health Revolution
	7.5 Challenges in Digital Health
		7.5.1 Multidisciplinary Collaboration
		7.5.2 Dissociated Technological, Institutional and Regulatory Frameworks
		7.5.3 Data Governance
		7.5.4 Economic and Financial Considerations
		7.5.5 Cultural, Social and Local Infrastructure Issues
		7.5.6 Human Rights, Ethical and Policy Challenges
			7.5.6.1 Security and Confidentiality of Data
			7.5.6.2 Trust
			7.5.6.3 Accountability
		7.5.7 COVID-19 Challenges and Digital Health
			7.5.7.1 Digital Health and COVID-19, Community Health Reactions
			7.5.7.2 Digital Communication During the Pandemic
			7.5.7.3 Digital Data to Classical COVID-19 Blowout, Progression and Awareness
	7.6 Future Research
	7.7 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 8: An Overview of Artificial Intelligence for Advanced Healthcare Systems
	8.1 Introduction
	8.2 Subdomain-based AI Applications in Healthcare Systems
		8.2.1 Machine Learning
		8.2.2 Deep Learning
		8.2.3 Natural Language Processing
		8.2.4 Rule-based Expert Systems
		8.2.5 Robotics
	8.3 Areas of Applicability of AI
		8.3.1 Administrative Level Applications
		8.3.2 Diagnostic Support
		8.3.3 Other Application Areas
	8.4 Combinational Applications of AI
		8.4.1 Artificial Intelligence for IoT-based Healthcare Application
		8.4.2 Blockchain for AI in Healthcare Applications
		8.4.3 Other Major Combination Applications of AI
	8.5 Discussions
	8.6 Conclusion
	8.7 Future Scope
	References
Chapter 9: Future Trajectory of Healthcare with Artificial Intelligence
	9.1 Introduction
		9.1.1 Overview of AI in Healthcare
		9.1.2 Machine Learning (ML) in Healthcare
		9.1.3 Deep Learning (DL) in Healthcare
		9.1.4 Real-Time Health Monitoring
	9.2 Role of AI in Robotic Surgery, Cancer Diagnosis and BCI
		9.2.1 Role of AI in Robotic Surgery
		9.2.2 Pre-operative Planning
		9.2.3 Intra-Operative Guidance
		9.2.4 Surgical Robots
		9.2.5 Role of AI in Cancer Diagnosis
		9.2.6 Role of AI in Brain Computer Interface
	9.3 Role of AI in Maintaining the Patient Database
		9.3.1 Overview of Electronic Health Record
		9.3.2 Technologies Involved in EHR
		9.3.3 Tools Used in EHR
		9.3.4 Security in EHR
		9.3.5 m-Health in EHR
	9.4 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 10: Artificial Intelligence and Public Trust on Smart Healthcare Systems
	10.1 Introduction
	10.2 Literature Review
		10.2.1 Artificial Intelligence
		10.2.2 AI in Healthcare
		10.2.3 Antecedents of Trust
		10.2.4 AI-Empowered Healthcare’s Expertise and Public Trust
		10.2.5 AI-Empowered Healthcare’s Performance and Public Trust
		10.2.6 AI-Empowered Healthcare’s Reputation and Public Trust
		10.2.7 AI-Empowered Healthcare’s Integrity and Public Trust
		10.2.8 AI-Empowered Healthcare’s Benevolence and Public Trust
	10.3 Research Method
		10.3.1 Sampling Technique
		10.3.2 Data Collection
		10.3.3 Data Analysis
	10.4 Results
		10.4.1 Exploratory Factor Analysis
		10.4.2 Indicators of Model Fit for Measurement Model
		10.4.3 Construct Validity
		10.4.4 Results of Path Analysis
	10.5 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 11: Role of Artificial Intelligence-Based Technologies in Healthcare to Combat Critical Diseases
	11.1 Introduction
	11.2 What AI Can Do for Health
		11.2.1 Prevention and Diagnosis Using AI
		11.2.2 Monitoring and Detection of Diseases
			11.2.2.1 Detection of Cancer
	11.3 Role of Medical Imaging and Deep Learning
	11.4 Role of Machine Learning (ML)
	11.5 Digital Health Transformation Using AI
	11.6 Digital Health Transformation Using Blockchain
	11.7 AI Applications for COVID-19
	11.8 Industrial Innovation in the Field of AI
		11.8.1 Types of Commercial-based AI technologies
	11.9 Challenges and Future Outlooks
	11.10 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 12: Parkinson’s Disease Pre-Diagnosis Using Smart Technologies: A Review
	12.1 Introduction
	12.2 Parkinson’s Disease Symptoms
	12.3 Diagnosis Markers
		12.3.1 Voice Markers
		12.3.2 Drawing Markers
		12.3.3 Keyboard Tapping Markers
		12.3.4 Gait Markers
		12.3.5 Multi-Marker Approaches
	12.4 Discussions
		12.4.1 Recommendations for Future Works
	12.5 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 13: Emerging Technologies to Combat the COVID-19 Pandemic
	13.1 Introduction
	13.2 COVID-19 Preventive Measures
	13.3 Smart Healthcare and New Technologies
		13.3.1 Telemedicine Facing COVID-19
		13.3.2 Internet of Things in Healthcare
		13.3.3 Drone Technology
		13.3.4 Robotics Technology
		13.3.5 Mobile Applications
		13.3.6 Artificial Intelligence (AI)
	13.4 Conclusion and Discussion
	Conflict of Interest
	Funding
	Data Availability
	References
Chapter 14: The Role of Machine Learning and Internet of Things in Digital Health Transformation
	14.1 Introduction
	14.2 IoT and ML Applications for SC
		14.2.1 Environmental Monitoring
		14.2.2 Smart Parking
		14.2.3 Traffic Monitoring
		14.2.4 Smart Education
		14.2.5 Smart Health
		14.2.6 Smart Buildings
		14.2.7 Smart Agriculture
	14.3 IoT Challenges in SC
	14.4 Secured SCs
	14.5 Conclusion
		14.5.1 Future Scope
	References
Chapter 15: Effective Remote Healthcare and Telemedicine Approaches for Improving Digital Healthcare Systems
	15.1 Introduction
		15.1.1 Chapter Organization
		15.1.2 Telemedicine History
		15.1.3 Telehealth and Telemedicine Consultation Centre
			15.1.3.1 Components
			15.1.3.2 Benefits of Telemedicine
		15.1.4 Telemedicine and Use of Artificial Intelligence
		15.1.5 Digital Health Transformation Using AI
			15.1.5.1 Digital Health Transformation through Blockchain
		15.1.6 Telemedicine through Cloud Computing
		15.1.7 Telemedicine and Blockchain
		15.1.8 Motivation
	15.2 Method
		15.2.1 AI-Based Bot
		15.2.2 Cloud-Enabled Interface
		15.2.3 Blockchain Interface
	15.3 Working of IAISTM Model
		15.3.1 Dataset
		15.3.2 Effectiveness of Telemedicine in Present Context
		15.3.3 Decision-Making System
		15.3.4 Summary of Telemedicine Model for Malaria
		15.3.5 Benefits of Cloud in Telemedicine
	15.4 Remote Monitoring Through IAISTM
		15.4.1 Benefits of IAISTM
		15.4.2 Wonders of AI and Blockchain
	15.5 Sustainability of the Work
	15.6 Application
	15.7 Conclusion
		15.7.1 Future Scope
	References
Chapter 16: Legal Implication of Blockchain Technology in Public Health
	16.1 Introduction
	16.2 Effectiveness of Blockchain towards Public Health
		16.2.1 Blockchain Influx with Time
		16.2.2 Smart Contract and Smart Consent
	16.3 Blockchain Laws around The Globe
		16.3.1 Laws of the United Kingdom and European Union
		16.3.2 Laws of the United States of America
		16.3.3 Laws of India
		16.3.4 Laws of Singapore
	16.4 Dynamics of Blockchain and Trust Mechanism
		16.4.1 Ethics Code
		16.4.2 Trust vs. Nationality
		16.4.3 Rationality and Absolute ‘Public Trust’
		16.4.4 Acceptance of Blockchain
	16.5 Blockchain and Data Governance
	16.6 Conclusion
	Conflict of Interest
	Funding
	Data Availability
	References
Index