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Submit a ProposalArtificial Intelligence in Healthcare for the Elderly
 | Edited by Sandeep Sharma, Preeti Nagrath, Bhawna Singla, and Joel J.P.C. Rodrigues Copyright: 2025 | Expected Pub Date:2025// ISBN: 9781394275366 | Hardcover | 414 pages Price: $225 USD  |
One Line Description
Artificial Intelligence in Healthcare for the Elderly provides valuable insights into how artificial intelligence can transform healthcare through personalized monitoring, ethical considerations, and real-world applications.
Audience
Researchers, students and teachers, technological developers, and healthcare professionals interested in innovative technology in elderly care
Researchers, students and teachers, technological developers, and healthcare professionals interested in innovative technology in elderly care
Description
Artificial intelligence has the potential to revolutionize healthcare for the elderly by providing efficient and personalized monitoring and care. Though this technology has the potential to revolutionize care, there is currently little information on the potential of this technology in elderly healthcare. Artificial Intelligence in Healthcare for the Elderly explores AI algorithms that can transform health monitoring for older adults by analyzing data from wearable devices, electronic health records, and other sources that provide real-time data analysis, detect early warning signs of diseases, and offer personalized treatment. This book addresses the critical ethical, societal, and practical aspects of elderly care that are often overlooked with insights from various disciplines, including healthcare, technology, ethics, and sociology, to offer a holistic perspective on AIs impact on aging. Artificial Intelligence in Healthcare for the Elderly offers an all-encompassing perspective on AI technologies employed in elderly healthcare by examining the specific types of technology used and delineating its role in elderly healthcare, drawing insights from existing research and case studies.
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Artificial intelligence has the potential to revolutionize healthcare for the elderly by providing efficient and personalized monitoring and care. Though this technology has the potential to revolutionize care, there is currently little information on the potential of this technology in elderly healthcare. Artificial Intelligence in Healthcare for the Elderly explores AI algorithms that can transform health monitoring for older adults by analyzing data from wearable devices, electronic health records, and other sources that provide real-time data analysis, detect early warning signs of diseases, and offer personalized treatment. This book addresses the critical ethical, societal, and practical aspects of elderly care that are often overlooked with insights from various disciplines, including healthcare, technology, ethics, and sociology, to offer a holistic perspective on AIs impact on aging. Artificial Intelligence in Healthcare for the Elderly offers an all-encompassing perspective on AI technologies employed in elderly healthcare by examining the specific types of technology used and delineating its role in elderly healthcare, drawing insights from existing research and case studies.
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Author / Editor Details
Sandeep Sharma, PhD is an assistant professor in Bharati Vidyapeeth’s College of Engineering. He has published more than 15 research papers in reputed journals and one patent. His main area of focus is the use of heuristic techniques for finding the optimal parameters of FACTS devices in power systems.
Sandeep Sharma, PhD is an assistant professor in Bharati Vidyapeeth’s College of Engineering. He has published more than 15 research papers in reputed journals and one patent. His main area of focus is the use of heuristic techniques for finding the optimal parameters of FACTS devices in power systems.
Preeti Nagrath, PhD is an associate professor in Bharati Vidyapeeth’s College of Engineering with more than 20 years of academic experience. She has published over 80 research papers in international journals and international conferences, four books, and two patents. His research interests include network security, delay-tolerant networks, machine learning, and deep learning.
Bhawna Singla, PhD is a professor in the Computer Science and Engineering Department at the Panipat Institute of Engineering and Technology. She has published two edited books, three patents, and 30 research articles in international journals and conferences. His research interests include artificial intelligence, machine learning, data science, and networking
Joel J. P. C. Rodrigues is a professor in the College of Computer Science and Technology at the China University of Petroleum, a senior researcher at the Instituto de Telecomunicações in Portugal, and a collaborator for the post-graduation program on teleinformatics engineering at the Federal University of Ceará in Brazil. He has authored and co-authored over 950 papers in refereed international journals and conferences, three books, and two patents. His research interests include sensor networks, Internet of Things, eHealth, vehicular networks, and cloud computing.
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Table of Contents
Preface
1. Smart Aging: Harnessing Artificial Intelligence in Elderly Healthcare
S.C. Vetrivel, V. Sabareeshwari, Ramya Ambikapathi, V.P. Arun and K.C. Sowmiya
1.1 Introduction
1.1.1 Overview of AI Applications in Healthcare
1.1.2 Importance of AI in Addressing Healthcare Challenges for the Elderly
1.2 Demographics and Aging Population
1.2.1 Statistics on the Aging Population
1.2.2 Healthcare Implications and Challenges of an Aging Society
1.3 Healthcare Needs of the Elderly
1.3.1 Common Health Issues Among the Elderly
1.3.2 Unique Challenges in Providing Healthcare for Seniors
1.4 Current Healthcare Technologies for the Elderly
1.4.1 Overview of Existing Healthcare Technologies
1.4.2 Limitations and Gaps in Current Solutions
1.5 AI in Diagnostics and Early Detection
1.5.1 Use of AI for Early Detection of Diseases
1.5.2 Diagnostic Applications in Geriatric Medicine
1.6 Remote Monitoring and Telehealth
1.6.1 AI-Enabled Remote Monitoring for the Elderly
1.6.2 Telehealth Solutions and Their Impact on Elderly Care
1.7 Personalized Medicine for the Elderly
1.7.1 Tailoring Healthcare Interventions Based on Individual Characteristics
1.7.2 AI Applications in Personalized Treatment Plans
1.8 Cognitive Assistance and Mental Health
1.8.1 AI Solutions for Cognitive Assistance
1.8.2 Addressing Mental Health Challenges in the Elderly through AI
1.9 Ethical Considerations and Privacy Issues
1.9.1 Ethical Challenges in Implementing AI in Healthcare
1.9.2 Ensuring Privacy and Security in AI-Powered Healthcare for the Elderly
1.10 Integration of AI into Healthcare Systems
1.10.1 Challenges and Opportunities in Integrating AI into Existing Healthcare Infrastructure
1.10.2 Strategies for Successful Implementation
1.11 Future Trends and Innovations
1.11.1 Emerging Technologies in AI for Elderly Healthcare
1.12 Conclusion
References
2. Telehealth Use Among Older Adults During COVID 19
Ramkrishna Mondal
2.1 Introduction
2.2 Telehealth in Geriatrics
2.2.1 Patient Safety
2.2.1.1 Care Coordination
2.2.1.2 Fall Prevention and Home Safety
2.2.1.3 Medication Review
2.2.2 Remote Health Assessment
2.2.2.1 Functional Status
2.2.2.2 Frailty
2.2.2.3 Nutritional Status
2.2.2.4 Medicare Annual Wellness Visit
2.2.3 Chronic Disease Management
2.2.3.1 Dementia
2.2.3.2 Depression
2.2.3.3 Heart Failure (HF)
2.2.3.4 Diabetes Mellitus
2.2.3.5 Hypertension
2.3 Role of Telehealth During the COVID Pandemic for the Elderly
2.3.1 Telehealth SWOT Analysis
2.3.2 Implementation of Telehealth Use for Geriatrics
2.3.2.1 The COVID-19 Pandemic Has Significantly Impacted the Availability, Accessibility, Affordability, and Quality of Telehealth in Geriatric Care
2.3.2.2 Advantages, Disadvantages, Opportunities, and Threats of Telehealth Use in COVID-19-Related Geriatric Care
2.3.2.3 Consequences for Practice and Research Gaps
2.3.3 Telemedicine in the International Context and Its Use among Older Adults
2.3.4 Use of Telemedicine to Meet Healthcare Needs of Older Adults
2.3.4.1 Occupational Assessment
2.3.4.2 Occupational Intervention
2.3.4.3 Rehabilitation Counseling
2.3.4.4 Support for Caregivers
2.3.4.5 Activity Monitoring
2.4 Factor Affecting Utilization of Telehealth in the Elderly during COVID-19
2.4.1 Factor Affecting Utilization and Access
2.4.1.1 Access to COVID-Related Services
2.4.1.2 Access to Non-COVID-Related Services
2.4.1.3 Literacy and Education
2.4.1.4 Perceived Attitudes of Aging
2.4.1.5 Accommodation Challenges
2.4.1.6 Policies and Structures
2.4.1.7 Socio-Cultural
2.4.2 Factor Affecting Behavioral Intention
2.4.2.1 Theme: Facilitating Conditions
2.4.2.2 Theme: Performance Expectancy
2.4.2.3 Theme: Effort Expectancy
2.4.2.4 Theme: Social Influence
2.5 Experiences of Telehealth in the Elderly
2.5.1 Experiences in Elderly
2.5.1.1 Silver Linings During the Pandemic
2.5.1.2 Some Roadblocks to Success
2.5.2 Literature Review on Experiences
2.5.3 Key Messages Derived from the Literature
2.5.4 Telehealth Interventions
2.5.4.1 TCC Smartphone-Based Care Model
2.5.4.2 Mobile Integrated Health
2.5.4.3 HCWs
2.5.5 Various Other Countries’ Experiences
2.6 Perception of Telehealth Among Elderly and Physicians
2.7 Challenges and Barriers of Telehealth for the Elderly
2.7.1 Challenges of Telehealth for Elderly
2.7.1.1 E-Health Services
2.7.1.2 Access to Necessary Resources During Self-Isolation
2.7.1.3 A Portion of the Canadian Government’s COVID-19
2.7.1.4 Long-Term Care Facilities (LTCFs)
2.7.1.5 Consequences of Self-Isolation on the Body and Mind
2.7.1.6 Neglect of Older Individuals, Ageism, and Age Discrimination
2.7.2 Barriers to Telehealth
2.7.2.1 Patient Barriers
2.7.2.2 Clinician Barriers
2.7.2.3 Structural and Social Determinants of Health Barriers
2.7.2.4 Caregivers
2.7.2.5 User-Centered Design in the Development of Telehealth Products
2.7.2.6 Structural and Organizational Strategies
2.7.3 Overcoming Barriers to Telemedicine Care
2.7.3.1 User-Specific Considerations
2.7.3.2 Technology-Specific Considerations
2.7.3.3 Financial Impact and Reimbursement Policies
2.7.3.4 Telemedicine Using Solely Audio
2.7.3.5 Extension of Services Added During the Pandemic
2.8 Future Direction and Lesson Learned
2.9 Conclusion
References
3. IoT for Seniors: How Technology Improves Quality of Life of Older Adults
Jyoti Agarwal, Wazih Ahmad, Imtiyazul Haq, Anu Saxena and T. Gopi Krishna
3.1 Introduction to IoT for Seniors
3.1.1 Understanding IoT
3.1.2 Relevance of IoT for Seniors
3.2 Smart Home Devices for Seniors
3.2.1 Smart Thermostat
3.2.2 Smart Lighting
3.2.3 Voice-Activated Assistants
3.3 Health and Wellness Monitoring
3.3.1 Wearable Devices
3.3.2 Health Tracking Apps
3.3.3 Remote Health Monitoring System
3.4 Security and Safety of Seniors
3.4.1 Telemedicine and Remote Consultation
3.4.2 Medication Management System
3.4.3 IoT in Assisted Living Facilities
3.5 Social Connectivity through IoT
3.5.1 Video Calling and Social Apps
3.5.2 Online Communities for Seniors
3.6 Adapting Existing Devices for Seniors
3.6.1 Making Standard Devices Senior-Friendly
3.6.2 Accessibility Features in IoT Devices
3.6.3 Privacy Measures for Seniors
3.6.4 Educating Seniors on Security
3.7 Overcoming Technological Barriers
3.7.1 Simplifying User Interfaces
3.7.2 Providing Tech Support for Seniors
3.8 Future Trends in IoT for Seniors
3.8.1 An Architectural Framework for Elderly Health Monitoring
3.9 Conclusion
References
4. AI and Robotics in Elderly Personal Assistance: Fostering Independent Living
Divya Udayan J. and Umashankar Subramaniam
4.1 Introduction
4.2 Personalization in Elderly Healthcare
4.2.1 Requirements for Personalized Assistance in Elderly Care
4.2.2 Customization Standards for Personalization
4.3 Design of an Adaptive Real-Time Intervention System for Elderly in Ambient Assisted Living
4.3.1 Visual Perception and Self-Localization
4.3.2 Context Awareness and Personalization
4.3.2.1 Context-Aware Multi-User Activity Recognition
4.3.2.2 Active Learning-Based Multi-User Activity Recognition
4.3.3 Activity Analysis and Risk Detection
4.3.3.1 Human Activity Recognition (HAR)
4.3.3.2 Behavioral Patterns Analysis
4.3.3.3 Personalized Assistance
4.3.4 Response Actions as Personalized Assistance
4.3.4.1 Inter-Module Communication
4.4 Effectiveness of Social Robots in Improving Independence of Elderly
4.4.1 Real-Time Examples: Socially Assistive Robots in Promoting Personalization
4.4.1.1 Effectiveness in Enhancing Independence
4.4.1.2 Personalization for Optimized Care
4.5 Conclusion
References
5. Enabling Independence of Elderly People Using IoT Technology
Raghav Pasrija, Sandeep Banerjee, Sandeep Sharma and Viktória Schneider
5.1 Introduction
5.2 Comprehending IoT: Development and Omnipresence
5.2.1 Evolution of IoT Throughout History
5.2.2 The Widespread Presence of IoT in Modern Society
5.3 Challenges Encountered by Elderly Individuals
5.3.1 Physical Health Challenges
5.3.2 Challenges Related to Cognition and Mental Health
5.3.3 Economic and Societal Obstacles
5.4 Constraints of Conventional Approaches
5.4.1 Facilities for Institutional Care
5.4.2 Home Care Services
5.4.3 Challenges in the Healthcare System
5.4.4 Cultural and Linguistic Obstacles
5.5 Incorporating Internet of Things Technology into Elderly Care
5.6 Advancement and Future Research
5.7 Summary and Future Prospects
5.7.1 Key Findings Summary
5.7.2 Prospective Avenues
5.8 Conclusion
References
6. Intersection of AI Tools and Application for Elderly Healthcare
Priyanka Suyal, Camellia Chakraborty, Kamal Kumar Gola, Mridula, Pavel Skrabanek, Sagar Gulati and Rajdeep Jung
6.1 Introduction to the Health Tech Landscape
6.1.1 Overview of AI and Emerging Technologies
6.1.2 AI in Healthcare Applications
6.2 AI-Driven Diagnostics, Imaging and Robotics
6.2.1 Importance of Medical Imaging in Diagnosing Age-Related Diseases
6.2.2 Advancements in Medical Imaging through Artificial Intelligence
6.2.3 Robotics in Surgery and Beyond for Elderly
6.2.4 Exoskeletons: Empowering Mobility for Elderly
6.3 Remote Healthcare Solutions for Elderly Well-Being
6.3.1 Telehealth and Remote Patient Monitoring (RPM)
6.3.2 Remote Monitoring and AI Predictive Analytics for Elderly
6.3.3 Mental Health Support and Social Interaction for the Elderly
6.4 Wearable Health Devices and Medication Management for the Elderly
6.4.1 Wearable Devices
6.4.2 Advances in Smart Devices for Symptom Monitoring
6.4.3 Intelligent Medication Management Systems
6.4.3.1 Compensation Strategies
6.4.3.2 Technology-Mediated Strategies
6.5 AI-Based Pain Management Strategies for Elderly Patients
6.5.1 Enhanced Pain Assessment Capabilities
6.5.2 Predictive Analytics and Clinical Decision Support
6.5.3 Empowering Self-Management through Digital Interventions
6.6 Future Directions and Ethical Considerations in AI-Driven Elderly Healthcare
6.6.1 Key Areas of Potential and Future Trends
6.6.2 Challenges and Considerations
6.6.3 Ethical Considerations
6.6.3.1 Concerns Regarding Beneficence
6.6.3.2 Challenges Related to Respect for Autonomy
6.6.3.3 Issues Surrounding Justice
6.6.3.4 Privacy and Confidentiality
6.6.3.5 Transparency and Accountability
6.7 Medicare Cataloging Based on AI Technology
6.8 Conclusion
References
7. Technological Impact on Nutrition Management of Adults
S.C. Vetrivel, V. Sabareeshwari, Ramya Ambikapathi, V.P. Arun and K.C. Sowmiya
7.1 Introduction
7.1.1 Intersection of Technology and Nutrition
7.1.2 Historical Perspective on the Evolution of Technology in Nutrition Management
7.2 Emerging Technologies in Food Production
7.2.1 Genetic Engineering and Its Impact on Food Quality
7.2.2 Precision Agriculture and Sustainable Farming Practices
7.2.3 Objectives
7.3 Digital Health and Nutrition Tracking Apps
7.3.1 Overview of Popular Nutrition Tracking Apps
7.3.2 Benefits and Limitations of Digital Tracking for Dietary Management
7.4 Smart Kitchen Appliances and Gadgets
7.4.1 Integration of Technology in Cooking and Meal Preparation
7.4.2 Smart Kitchen Devices for Portion Control and Healthy Cooking
7.5 Nutrigenomics and Personalized Nutrition
7.5.1 Understanding the Role of Genetics in Nutrition
7.5.2 Personalized Nutrition Plans Based on Genetic Information
7.6 Telehealth and Remote Nutrition Counseling
7.6.1 Remote Access to Nutrition Experts through Technology
7.6.2 Virtual Consultations and Monitoring for Dietary Management
7.7 Wearable Technology for Fitness and Nutrition
7.7.1 Fitness Trackers and Their Impact on Physical Activity and Diet
7.7.2 Smart Wearables for Real-Time Health Monitoring
7.8 Augmented Reality in Nutrition Education
7.8.1 AR Applications for Nutrition Education and Awareness
7.8.2 Interactive Experiences for Learning About Food Choices and Portion Control
7.9 Blockchain in the Food Supply Chain
7.9.1 Ensuring Transparency and Traceability in the Food Supply
7.9.2 Reducing Food Fraud and Improving Food Safety through Blockchain
7.10 Challenges and Ethical Considerations
7.10.1 Addressing Privacy Concerns in Health and Nutrition Technology
7.10.2 Ethical Considerations in the Use of Emerging Technologies
7.11 Future Trends in Technological Nutrition Management
7.11.1 Predicting Future Developments in Technology and Nutrition
7.11.2 Potential Breakthroughs and Their Impact on Adult Nutrition
7.12 Conclusion
References
8. Empowering Nutrition and Diet of Elderly People Using Digital Technology
Shiva Tushir, Navidha Aggarwal, Himanshu Sehrawat and Sabina Yasmin
8.1 Understanding Nutrition
8.1.1 Definition of Nutrition
8.1.2 Macronutrients and Micronutrients
8.2 Various Types of Macronutrients and Micronutrients
8.2.1 Proteins
8.2.2 Carbohydrates
8.2.3 Fats
8.2.4 Micronutrients
8.2.5 Vitamins and Minerals
8.2.6 Hydration
8.2.7 Phytonutrients
8.2.8 Water and Hydration
8.3 Nutrient Absorption and Metabolism
8.3.1 Enhancement of Bioavailability
8.3.2 Nutrition Tracking and Smartphone Applications
8.3.3 Nutraceuticals and Functional Foods
8.3.4 Gut Microbiota and Nutrition Utilization
8.3.5 Artificial Intelligence in Nutrition Analysis
8.3.6 Medical Technologies for Nutrient Administration
8.4 Key Concepts and Terminology Related to Nutrition
8.4.1 Concepts of Nutrition
8.4.2 Nutritional Concept
8.4.3 Nutrition for Clinical Practice
8.4.4 Undernourishment
8.4.5 Malnutrition Linked to Disease (DRM) Combined with Inflammation
8.4.6 Importance of Nutrition Management
8.4.6.1 Disease Prevention and Health Promotion
8.4.6.2 Body Composition and Weight Management
8.4.6.3 Enhancing Performance and Maintaining Physical Fitness
8.4.6.4 Mental Health and Cognitive Function
8.5 Fundamentals of Technology
8.5.1 Data Gathering and Analysis
8.5.2 Nutrition Tracking Apps
8.5.3 Diet Plan Apps
8.5.4 Nutrition-Related Education
8.5.5 Precision Approach of Nutrition
8.5.6 Telehealth and Remote Monitoring
8.6 Introduction to Technology
8.7 Need of Technology for Health
8.7.1 Incremental Analysis
8.7.2 Accessible Information
8.7.3 Filling of Communication Gap
8.7.4 Highly Efficient and Cost Effective
8.7.5 Personalized Nutrition Approach
8.7.6 Public Health Nutrition Concern
8.7.7 Preventive Health Care
8.7.8 Empowering People with Chronic Issues
8.7.9 Closing the Healthcare Access Gap
8.8 Technology for Disease Management in COVID-19
8.9 Technological Interventions for Self-Care
8.10 Artificial Intelligence
8.10.1 Personalized Nutrition Recommendations
8.10.2 Nutritional Analysis
8.10.3 Nutritional Content Prediction
8.10.4 Behavioral Analysis and Coaching
8.10.5 Disease Risk Prediction and Prevention
8.10.6 Chatbots and Virtual Assistants Driven by Artificial Intelligence
8.10.7 Food Supply Chain Optimization
8.11 Deep Learning
8.11.1 Customized Evaluation of Food Consumption
8.11.2 Nutrition Advice and Customized Meal Planning
8.11.3 Predicting and Managing Disease Risk
8.11.4 Analysis of Food Behavior and Habits
8.11.5 Motivational Tools and Gamification
8.12 Machine Learning
8.12.1 Food and Nutrient Intake Tracking
8.12.2 Coaching and Modification of Behavior
8.12.3 Customized Food Delivery Services
8.12.4 Disease Identification and Prevention
8.12.5 Nutritional Profile
8.12.6 Gut Health Analysis
8.12.7 Health Prediction
8.13 Limitations of Machine Learning
8.13.1 Model Transparency
8.13.2 Accessibility
8.13.3 Regulation and Supervision
8.13.4 Integration with Other Technologies
8.13.5 Emphasis on Behavior Modification
8.13.6 Cooperation between Varied Stakeholders
8.14 Role of Various Technological Interventions in Self-Care
8.15 Possible Advantages
8.15.1 Improved Access
8.15.2 Active Engaging
8.15.3 Data Collection and Health Monitoring
8.15.4 Enhanced Health Support
8.16 Possible Limitations
8.16.1 Digital Gap
8.16.2 Privacy
8.16.3 Over-Reliance
8.16.4 Accessible to Users
8.16.5 Misidentification
References
9. Healthcare 4.0: Healthcare in Technological World
Manoj Kumar Mahto, Durgesh Srivastava and Santosh Kumar Srivastava
9.1 Introduction
9.1.1 The Silver Tsunami and Its Challenges for Healthcare
9.1.2 Healthcare 4.0: A Technological Revolution for Elder Care
9.1.3 The Promise of AI, Big Data, and the Internet of Things (IoT)
9.2 AI-Powered Tools for Proactive Healthcare and Chronic Disease Management
9.2.1 Early Disease Detection and Risk Prediction
9.2.2 Personalized Health Education and Support with AI Chatbots
9.2.3 Remote Monitoring and Proactive Intervention for Chronic Conditions
9.3 Transforming Remote Care with Telehealth and Connected Devices
9.3.1 Smart Homes and Wearables for Real-Time Vital Sign Monitoring
9.3.2 Telehealth Platforms for Virtual Consultations and Remote Diagnosis
9.3.3 AI-Powered Virtual Companions and Social Robots for Combating Loneliness
9.4 Personalized Care Plans and Decision Support Systems
9.4.1 Tailored Treatment Recommendations and Medication Schedules
9.4.2 AI-Driven Decision Support Systems for Healthcare Professionals
9.4.3 Ethical Considerations and Transparency in AI-Based Healthcare
9.5 Challenges and Opportunities: Ethical Considerations and Future Directions
9.5.1 Data Privacy and Security Concerns in Healthcare 4.0
9.5.2 Bridging the Digital Divide for Equitable Access to Technology
9.5.3 Mitigating Bias and Discrimination in AI-Powered Healthcare
9.5.4 Human-Centric Design and the Importance of Patient Autonomy
9.6 Conclusion: A Future of Empowered and Accessible Elder Care
9.6.1 The Potential of Healthcare 4.0 to Improve Quality of Life and Care Outcomes
9.6.2 Fostering Collaboration and Accountable Development of AI in Healthcare
9.6.3 A Vision for a Future Where Technology Empowers, Not Replaces, Human Care
References
10. Ethical Considerations in AI-Powered Nutrition Guidance: Balancing Privacy, Data Security, and Bias Mitigation
Shweta Saraswat, Vrishit Saraswat, Kamalkant Jain and Shourya Sharma
10.1 Introduction
10.1.1 Background
10.1.2 Objectives of AI-Powered Nutrition Guidance
10.1.3 Importance of Ethical Considerations
10.2 Privacy Concerns in AI-Powered Nutrition Guidance
10.2.1 Collection of Personal Data
10.2.2 Transparency and Informed Consent
10.2.3 Data Ownership
10.2.4 Striking the Balance between Personalization and Privacy
10.3 Data Security in AI-Powered Nutrition Guidance
10.3.1 Ensuring the Protection of Personal and Health Data
10.3.2 Encryption Techniques
10.3.3 Secure Storage Solutions
10.3.4 Periodic Security Audits
10.4 Bias Mitigation in AI-Powered Nutrition Guidance
10.4.1 Understanding Bias in AI Systems
10.4.2 Scrutinizing Data Sources
10.4.3 Algorithmic Decision Making
10.4.4 Continuous Monitoring and Adjustment
10.5 Recommendations and Best Practices
10.6 Case Studies
10.6.1 Ethical Challenges Faced by Existing AI-Powered Nutrition Platforms
10.6.2 Successful Implementation of Ethical Guidelines
10.7 Future Perspectives
10.7.1 Evolving Ethical Standards
10.7.2 Technological Advances in Privacy, Security, and Bias Mitigation
10.8 Conclusion
References
11. Prevention of Blindness for Diabetic Patients Using Deep Learning Techniques
U. Sadhana, Beena B.M. and Prashanth C. Ranga
11.1 Introduction
11.2 Related Works
11.3 Case Studies of Diabetic Retinopathy
11.4 Techniques to Detect Diabetic Retinopathy
11.5 Deep Learning Methods to Detect Diabetic Retinopathy
11.6 Dataset
11.7 Results
11.8 Conclusion
References
12. Transitioning to Healthcare 4.0: Embracing Digital Innovation for Enhanced Patient Care and Outcomes
Navjot Singh Talwandi, Shanu Khare and Payal Thakur
12.1 Understanding Healthcare 4.0
12.1.1 Definition and Overview of Healthcare 4.0
12.1.2 Evolution from Traditional Healthcare Models to Healthcare 4.0
12.2 Digital Transformation in Healthcare
12.2.1 The Role of Digital Technologies in Transforming Healthcare Delivery
12.2.2 Benefits and Advantages of Digital Transformation in Patient Care
12.3 Leveraging Artificial Intelligence (AI) in Patient Care
12.3.1 Applications of AI in Diagnostics and Treatment Planning
12.3.2 AI-Driven Personalized Medicine and Predictive Analytics
12.4 Internet of Things (IoT) in Healthcare
12.4.1 Connected Medical Devices and Wearable Technology
12.4.2 Remote Patient Monitoring and Real-Time Health Data Collection
12.5 Big Data Analytics for Healthcare Improvement
12.5.1 Utilizing Healthcare Data for Population Health Management
12.5.2 Predictive Analytics for Disease Prevention and Early Intervention
12.6 Telemedicine and Remote Care Services
12.6.1 Advantages of Telemedicine in Expanding Access to Healthcare Services
12.6.2 Remote Consultations and Virtual Care Delivery Models
12.7 Cybersecurity and Data Privacy in Healthcare 4.0
12.7.1 Challenges and Risks Associated with Digital Transformation in Healthcare
12.7.2 Importance of Cybersecurity Measures to Protect Patient Data
12.8 Conclusion
References
About the Editors
Index
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Preface
1. Smart Aging: Harnessing Artificial Intelligence in Elderly Healthcare
S.C. Vetrivel, V. Sabareeshwari, Ramya Ambikapathi, V.P. Arun and K.C. Sowmiya
1.1 Introduction
1.1.1 Overview of AI Applications in Healthcare
1.1.2 Importance of AI in Addressing Healthcare Challenges for the Elderly
1.2 Demographics and Aging Population
1.2.1 Statistics on the Aging Population
1.2.2 Healthcare Implications and Challenges of an Aging Society
1.3 Healthcare Needs of the Elderly
1.3.1 Common Health Issues Among the Elderly
1.3.2 Unique Challenges in Providing Healthcare for Seniors
1.4 Current Healthcare Technologies for the Elderly
1.4.1 Overview of Existing Healthcare Technologies
1.4.2 Limitations and Gaps in Current Solutions
1.5 AI in Diagnostics and Early Detection
1.5.1 Use of AI for Early Detection of Diseases
1.5.2 Diagnostic Applications in Geriatric Medicine
1.6 Remote Monitoring and Telehealth
1.6.1 AI-Enabled Remote Monitoring for the Elderly
1.6.2 Telehealth Solutions and Their Impact on Elderly Care
1.7 Personalized Medicine for the Elderly
1.7.1 Tailoring Healthcare Interventions Based on Individual Characteristics
1.7.2 AI Applications in Personalized Treatment Plans
1.8 Cognitive Assistance and Mental Health
1.8.1 AI Solutions for Cognitive Assistance
1.8.2 Addressing Mental Health Challenges in the Elderly through AI
1.9 Ethical Considerations and Privacy Issues
1.9.1 Ethical Challenges in Implementing AI in Healthcare
1.9.2 Ensuring Privacy and Security in AI-Powered Healthcare for the Elderly
1.10 Integration of AI into Healthcare Systems
1.10.1 Challenges and Opportunities in Integrating AI into Existing Healthcare Infrastructure
1.10.2 Strategies for Successful Implementation
1.11 Future Trends and Innovations
1.11.1 Emerging Technologies in AI for Elderly Healthcare
1.12 Conclusion
References
2. Telehealth Use Among Older Adults During COVID 19
Ramkrishna Mondal
2.1 Introduction
2.2 Telehealth in Geriatrics
2.2.1 Patient Safety
2.2.1.1 Care Coordination
2.2.1.2 Fall Prevention and Home Safety
2.2.1.3 Medication Review
2.2.2 Remote Health Assessment
2.2.2.1 Functional Status
2.2.2.2 Frailty
2.2.2.3 Nutritional Status
2.2.2.4 Medicare Annual Wellness Visit
2.2.3 Chronic Disease Management
2.2.3.1 Dementia
2.2.3.2 Depression
2.2.3.3 Heart Failure (HF)
2.2.3.4 Diabetes Mellitus
2.2.3.5 Hypertension
2.3 Role of Telehealth During the COVID Pandemic for the Elderly
2.3.1 Telehealth SWOT Analysis
2.3.2 Implementation of Telehealth Use for Geriatrics
2.3.2.1 The COVID-19 Pandemic Has Significantly Impacted the Availability, Accessibility, Affordability, and Quality of Telehealth in Geriatric Care
2.3.2.2 Advantages, Disadvantages, Opportunities, and Threats of Telehealth Use in COVID-19-Related Geriatric Care
2.3.2.3 Consequences for Practice and Research Gaps
2.3.3 Telemedicine in the International Context and Its Use among Older Adults
2.3.4 Use of Telemedicine to Meet Healthcare Needs of Older Adults
2.3.4.1 Occupational Assessment
2.3.4.2 Occupational Intervention
2.3.4.3 Rehabilitation Counseling
2.3.4.4 Support for Caregivers
2.3.4.5 Activity Monitoring
2.4 Factor Affecting Utilization of Telehealth in the Elderly during COVID-19
2.4.1 Factor Affecting Utilization and Access
2.4.1.1 Access to COVID-Related Services
2.4.1.2 Access to Non-COVID-Related Services
2.4.1.3 Literacy and Education
2.4.1.4 Perceived Attitudes of Aging
2.4.1.5 Accommodation Challenges
2.4.1.6 Policies and Structures
2.4.1.7 Socio-Cultural
2.4.2 Factor Affecting Behavioral Intention
2.4.2.1 Theme: Facilitating Conditions
2.4.2.2 Theme: Performance Expectancy
2.4.2.3 Theme: Effort Expectancy
2.4.2.4 Theme: Social Influence
2.5 Experiences of Telehealth in the Elderly
2.5.1 Experiences in Elderly
2.5.1.1 Silver Linings During the Pandemic
2.5.1.2 Some Roadblocks to Success
2.5.2 Literature Review on Experiences
2.5.3 Key Messages Derived from the Literature
2.5.4 Telehealth Interventions
2.5.4.1 TCC Smartphone-Based Care Model
2.5.4.2 Mobile Integrated Health
2.5.4.3 HCWs
2.5.5 Various Other Countries’ Experiences
2.6 Perception of Telehealth Among Elderly and Physicians
2.7 Challenges and Barriers of Telehealth for the Elderly
2.7.1 Challenges of Telehealth for Elderly
2.7.1.1 E-Health Services
2.7.1.2 Access to Necessary Resources During Self-Isolation
2.7.1.3 A Portion of the Canadian Government’s COVID-19
2.7.1.4 Long-Term Care Facilities (LTCFs)
2.7.1.5 Consequences of Self-Isolation on the Body and Mind
2.7.1.6 Neglect of Older Individuals, Ageism, and Age Discrimination
2.7.2 Barriers to Telehealth
2.7.2.1 Patient Barriers
2.7.2.2 Clinician Barriers
2.7.2.3 Structural and Social Determinants of Health Barriers
2.7.2.4 Caregivers
2.7.2.5 User-Centered Design in the Development of Telehealth Products
2.7.2.6 Structural and Organizational Strategies
2.7.3 Overcoming Barriers to Telemedicine Care
2.7.3.1 User-Specific Considerations
2.7.3.2 Technology-Specific Considerations
2.7.3.3 Financial Impact and Reimbursement Policies
2.7.3.4 Telemedicine Using Solely Audio
2.7.3.5 Extension of Services Added During the Pandemic
2.8 Future Direction and Lesson Learned
2.9 Conclusion
References
3. IoT for Seniors: How Technology Improves Quality of Life of Older Adults
Jyoti Agarwal, Wazih Ahmad, Imtiyazul Haq, Anu Saxena and T. Gopi Krishna
3.1 Introduction to IoT for Seniors
3.1.1 Understanding IoT
3.1.2 Relevance of IoT for Seniors
3.2 Smart Home Devices for Seniors
3.2.1 Smart Thermostat
3.2.2 Smart Lighting
3.2.3 Voice-Activated Assistants
3.3 Health and Wellness Monitoring
3.3.1 Wearable Devices
3.3.2 Health Tracking Apps
3.3.3 Remote Health Monitoring System
3.4 Security and Safety of Seniors
3.4.1 Telemedicine and Remote Consultation
3.4.2 Medication Management System
3.4.3 IoT in Assisted Living Facilities
3.5 Social Connectivity through IoT
3.5.1 Video Calling and Social Apps
3.5.2 Online Communities for Seniors
3.6 Adapting Existing Devices for Seniors
3.6.1 Making Standard Devices Senior-Friendly
3.6.2 Accessibility Features in IoT Devices
3.6.3 Privacy Measures for Seniors
3.6.4 Educating Seniors on Security
3.7 Overcoming Technological Barriers
3.7.1 Simplifying User Interfaces
3.7.2 Providing Tech Support for Seniors
3.8 Future Trends in IoT for Seniors
3.8.1 An Architectural Framework for Elderly Health Monitoring
3.9 Conclusion
References
4. AI and Robotics in Elderly Personal Assistance: Fostering Independent Living
Divya Udayan J. and Umashankar Subramaniam
4.1 Introduction
4.2 Personalization in Elderly Healthcare
4.2.1 Requirements for Personalized Assistance in Elderly Care
4.2.2 Customization Standards for Personalization
4.3 Design of an Adaptive Real-Time Intervention System for Elderly in Ambient Assisted Living
4.3.1 Visual Perception and Self-Localization
4.3.2 Context Awareness and Personalization
4.3.2.1 Context-Aware Multi-User Activity Recognition
4.3.2.2 Active Learning-Based Multi-User Activity Recognition
4.3.3 Activity Analysis and Risk Detection
4.3.3.1 Human Activity Recognition (HAR)
4.3.3.2 Behavioral Patterns Analysis
4.3.3.3 Personalized Assistance
4.3.4 Response Actions as Personalized Assistance
4.3.4.1 Inter-Module Communication
4.4 Effectiveness of Social Robots in Improving Independence of Elderly
4.4.1 Real-Time Examples: Socially Assistive Robots in Promoting Personalization
4.4.1.1 Effectiveness in Enhancing Independence
4.4.1.2 Personalization for Optimized Care
4.5 Conclusion
References
5. Enabling Independence of Elderly People Using IoT Technology
Raghav Pasrija, Sandeep Banerjee, Sandeep Sharma and Viktória Schneider
5.1 Introduction
5.2 Comprehending IoT: Development and Omnipresence
5.2.1 Evolution of IoT Throughout History
5.2.2 The Widespread Presence of IoT in Modern Society
5.3 Challenges Encountered by Elderly Individuals
5.3.1 Physical Health Challenges
5.3.2 Challenges Related to Cognition and Mental Health
5.3.3 Economic and Societal Obstacles
5.4 Constraints of Conventional Approaches
5.4.1 Facilities for Institutional Care
5.4.2 Home Care Services
5.4.3 Challenges in the Healthcare System
5.4.4 Cultural and Linguistic Obstacles
5.5 Incorporating Internet of Things Technology into Elderly Care
5.6 Advancement and Future Research
5.7 Summary and Future Prospects
5.7.1 Key Findings Summary
5.7.2 Prospective Avenues
5.8 Conclusion
References
6. Intersection of AI Tools and Application for Elderly Healthcare
Priyanka Suyal, Camellia Chakraborty, Kamal Kumar Gola, Mridula, Pavel Skrabanek, Sagar Gulati and Rajdeep Jung
6.1 Introduction to the Health Tech Landscape
6.1.1 Overview of AI and Emerging Technologies
6.1.2 AI in Healthcare Applications
6.2 AI-Driven Diagnostics, Imaging and Robotics
6.2.1 Importance of Medical Imaging in Diagnosing Age-Related Diseases
6.2.2 Advancements in Medical Imaging through Artificial Intelligence
6.2.3 Robotics in Surgery and Beyond for Elderly
6.2.4 Exoskeletons: Empowering Mobility for Elderly
6.3 Remote Healthcare Solutions for Elderly Well-Being
6.3.1 Telehealth and Remote Patient Monitoring (RPM)
6.3.2 Remote Monitoring and AI Predictive Analytics for Elderly
6.3.3 Mental Health Support and Social Interaction for the Elderly
6.4 Wearable Health Devices and Medication Management for the Elderly
6.4.1 Wearable Devices
6.4.2 Advances in Smart Devices for Symptom Monitoring
6.4.3 Intelligent Medication Management Systems
6.4.3.1 Compensation Strategies
6.4.3.2 Technology-Mediated Strategies
6.5 AI-Based Pain Management Strategies for Elderly Patients
6.5.1 Enhanced Pain Assessment Capabilities
6.5.2 Predictive Analytics and Clinical Decision Support
6.5.3 Empowering Self-Management through Digital Interventions
6.6 Future Directions and Ethical Considerations in AI-Driven Elderly Healthcare
6.6.1 Key Areas of Potential and Future Trends
6.6.2 Challenges and Considerations
6.6.3 Ethical Considerations
6.6.3.1 Concerns Regarding Beneficence
6.6.3.2 Challenges Related to Respect for Autonomy
6.6.3.3 Issues Surrounding Justice
6.6.3.4 Privacy and Confidentiality
6.6.3.5 Transparency and Accountability
6.7 Medicare Cataloging Based on AI Technology
6.8 Conclusion
References
7. Technological Impact on Nutrition Management of Adults
S.C. Vetrivel, V. Sabareeshwari, Ramya Ambikapathi, V.P. Arun and K.C. Sowmiya
7.1 Introduction
7.1.1 Intersection of Technology and Nutrition
7.1.2 Historical Perspective on the Evolution of Technology in Nutrition Management
7.2 Emerging Technologies in Food Production
7.2.1 Genetic Engineering and Its Impact on Food Quality
7.2.2 Precision Agriculture and Sustainable Farming Practices
7.2.3 Objectives
7.3 Digital Health and Nutrition Tracking Apps
7.3.1 Overview of Popular Nutrition Tracking Apps
7.3.2 Benefits and Limitations of Digital Tracking for Dietary Management
7.4 Smart Kitchen Appliances and Gadgets
7.4.1 Integration of Technology in Cooking and Meal Preparation
7.4.2 Smart Kitchen Devices for Portion Control and Healthy Cooking
7.5 Nutrigenomics and Personalized Nutrition
7.5.1 Understanding the Role of Genetics in Nutrition
7.5.2 Personalized Nutrition Plans Based on Genetic Information
7.6 Telehealth and Remote Nutrition Counseling
7.6.1 Remote Access to Nutrition Experts through Technology
7.6.2 Virtual Consultations and Monitoring for Dietary Management
7.7 Wearable Technology for Fitness and Nutrition
7.7.1 Fitness Trackers and Their Impact on Physical Activity and Diet
7.7.2 Smart Wearables for Real-Time Health Monitoring
7.8 Augmented Reality in Nutrition Education
7.8.1 AR Applications for Nutrition Education and Awareness
7.8.2 Interactive Experiences for Learning About Food Choices and Portion Control
7.9 Blockchain in the Food Supply Chain
7.9.1 Ensuring Transparency and Traceability in the Food Supply
7.9.2 Reducing Food Fraud and Improving Food Safety through Blockchain
7.10 Challenges and Ethical Considerations
7.10.1 Addressing Privacy Concerns in Health and Nutrition Technology
7.10.2 Ethical Considerations in the Use of Emerging Technologies
7.11 Future Trends in Technological Nutrition Management
7.11.1 Predicting Future Developments in Technology and Nutrition
7.11.2 Potential Breakthroughs and Their Impact on Adult Nutrition
7.12 Conclusion
References
8. Empowering Nutrition and Diet of Elderly People Using Digital Technology
Shiva Tushir, Navidha Aggarwal, Himanshu Sehrawat and Sabina Yasmin
8.1 Understanding Nutrition
8.1.1 Definition of Nutrition
8.1.2 Macronutrients and Micronutrients
8.2 Various Types of Macronutrients and Micronutrients
8.2.1 Proteins
8.2.2 Carbohydrates
8.2.3 Fats
8.2.4 Micronutrients
8.2.5 Vitamins and Minerals
8.2.6 Hydration
8.2.7 Phytonutrients
8.2.8 Water and Hydration
8.3 Nutrient Absorption and Metabolism
8.3.1 Enhancement of Bioavailability
8.3.2 Nutrition Tracking and Smartphone Applications
8.3.3 Nutraceuticals and Functional Foods
8.3.4 Gut Microbiota and Nutrition Utilization
8.3.5 Artificial Intelligence in Nutrition Analysis
8.3.6 Medical Technologies for Nutrient Administration
8.4 Key Concepts and Terminology Related to Nutrition
8.4.1 Concepts of Nutrition
8.4.2 Nutritional Concept
8.4.3 Nutrition for Clinical Practice
8.4.4 Undernourishment
8.4.5 Malnutrition Linked to Disease (DRM) Combined with Inflammation
8.4.6 Importance of Nutrition Management
8.4.6.1 Disease Prevention and Health Promotion
8.4.6.2 Body Composition and Weight Management
8.4.6.3 Enhancing Performance and Maintaining Physical Fitness
8.4.6.4 Mental Health and Cognitive Function
8.5 Fundamentals of Technology
8.5.1 Data Gathering and Analysis
8.5.2 Nutrition Tracking Apps
8.5.3 Diet Plan Apps
8.5.4 Nutrition-Related Education
8.5.5 Precision Approach of Nutrition
8.5.6 Telehealth and Remote Monitoring
8.6 Introduction to Technology
8.7 Need of Technology for Health
8.7.1 Incremental Analysis
8.7.2 Accessible Information
8.7.3 Filling of Communication Gap
8.7.4 Highly Efficient and Cost Effective
8.7.5 Personalized Nutrition Approach
8.7.6 Public Health Nutrition Concern
8.7.7 Preventive Health Care
8.7.8 Empowering People with Chronic Issues
8.7.9 Closing the Healthcare Access Gap
8.8 Technology for Disease Management in COVID-19
8.9 Technological Interventions for Self-Care
8.10 Artificial Intelligence
8.10.1 Personalized Nutrition Recommendations
8.10.2 Nutritional Analysis
8.10.3 Nutritional Content Prediction
8.10.4 Behavioral Analysis and Coaching
8.10.5 Disease Risk Prediction and Prevention
8.10.6 Chatbots and Virtual Assistants Driven by Artificial Intelligence
8.10.7 Food Supply Chain Optimization
8.11 Deep Learning
8.11.1 Customized Evaluation of Food Consumption
8.11.2 Nutrition Advice and Customized Meal Planning
8.11.3 Predicting and Managing Disease Risk
8.11.4 Analysis of Food Behavior and Habits
8.11.5 Motivational Tools and Gamification
8.12 Machine Learning
8.12.1 Food and Nutrient Intake Tracking
8.12.2 Coaching and Modification of Behavior
8.12.3 Customized Food Delivery Services
8.12.4 Disease Identification and Prevention
8.12.5 Nutritional Profile
8.12.6 Gut Health Analysis
8.12.7 Health Prediction
8.13 Limitations of Machine Learning
8.13.1 Model Transparency
8.13.2 Accessibility
8.13.3 Regulation and Supervision
8.13.4 Integration with Other Technologies
8.13.5 Emphasis on Behavior Modification
8.13.6 Cooperation between Varied Stakeholders
8.14 Role of Various Technological Interventions in Self-Care
8.15 Possible Advantages
8.15.1 Improved Access
8.15.2 Active Engaging
8.15.3 Data Collection and Health Monitoring
8.15.4 Enhanced Health Support
8.16 Possible Limitations
8.16.1 Digital Gap
8.16.2 Privacy
8.16.3 Over-Reliance
8.16.4 Accessible to Users
8.16.5 Misidentification
References
9. Healthcare 4.0: Healthcare in Technological World
Manoj Kumar Mahto, Durgesh Srivastava and Santosh Kumar Srivastava
9.1 Introduction
9.1.1 The Silver Tsunami and Its Challenges for Healthcare
9.1.2 Healthcare 4.0: A Technological Revolution for Elder Care
9.1.3 The Promise of AI, Big Data, and the Internet of Things (IoT)
9.2 AI-Powered Tools for Proactive Healthcare and Chronic Disease Management
9.2.1 Early Disease Detection and Risk Prediction
9.2.2 Personalized Health Education and Support with AI Chatbots
9.2.3 Remote Monitoring and Proactive Intervention for Chronic Conditions
9.3 Transforming Remote Care with Telehealth and Connected Devices
9.3.1 Smart Homes and Wearables for Real-Time Vital Sign Monitoring
9.3.2 Telehealth Platforms for Virtual Consultations and Remote Diagnosis
9.3.3 AI-Powered Virtual Companions and Social Robots for Combating Loneliness
9.4 Personalized Care Plans and Decision Support Systems
9.4.1 Tailored Treatment Recommendations and Medication Schedules
9.4.2 AI-Driven Decision Support Systems for Healthcare Professionals
9.4.3 Ethical Considerations and Transparency in AI-Based Healthcare
9.5 Challenges and Opportunities: Ethical Considerations and Future Directions
9.5.1 Data Privacy and Security Concerns in Healthcare 4.0
9.5.2 Bridging the Digital Divide for Equitable Access to Technology
9.5.3 Mitigating Bias and Discrimination in AI-Powered Healthcare
9.5.4 Human-Centric Design and the Importance of Patient Autonomy
9.6 Conclusion: A Future of Empowered and Accessible Elder Care
9.6.1 The Potential of Healthcare 4.0 to Improve Quality of Life and Care Outcomes
9.6.2 Fostering Collaboration and Accountable Development of AI in Healthcare
9.6.3 A Vision for a Future Where Technology Empowers, Not Replaces, Human Care
References
10. Ethical Considerations in AI-Powered Nutrition Guidance: Balancing Privacy, Data Security, and Bias Mitigation
Shweta Saraswat, Vrishit Saraswat, Kamalkant Jain and Shourya Sharma
10.1 Introduction
10.1.1 Background
10.1.2 Objectives of AI-Powered Nutrition Guidance
10.1.3 Importance of Ethical Considerations
10.2 Privacy Concerns in AI-Powered Nutrition Guidance
10.2.1 Collection of Personal Data
10.2.2 Transparency and Informed Consent
10.2.3 Data Ownership
10.2.4 Striking the Balance between Personalization and Privacy
10.3 Data Security in AI-Powered Nutrition Guidance
10.3.1 Ensuring the Protection of Personal and Health Data
10.3.2 Encryption Techniques
10.3.3 Secure Storage Solutions
10.3.4 Periodic Security Audits
10.4 Bias Mitigation in AI-Powered Nutrition Guidance
10.4.1 Understanding Bias in AI Systems
10.4.2 Scrutinizing Data Sources
10.4.3 Algorithmic Decision Making
10.4.4 Continuous Monitoring and Adjustment
10.5 Recommendations and Best Practices
10.6 Case Studies
10.6.1 Ethical Challenges Faced by Existing AI-Powered Nutrition Platforms
10.6.2 Successful Implementation of Ethical Guidelines
10.7 Future Perspectives
10.7.1 Evolving Ethical Standards
10.7.2 Technological Advances in Privacy, Security, and Bias Mitigation
10.8 Conclusion
References
11. Prevention of Blindness for Diabetic Patients Using Deep Learning Techniques
U. Sadhana, Beena B.M. and Prashanth C. Ranga
11.1 Introduction
11.2 Related Works
11.3 Case Studies of Diabetic Retinopathy
11.4 Techniques to Detect Diabetic Retinopathy
11.5 Deep Learning Methods to Detect Diabetic Retinopathy
11.6 Dataset
11.7 Results
11.8 Conclusion
References
12. Transitioning to Healthcare 4.0: Embracing Digital Innovation for Enhanced Patient Care and Outcomes
Navjot Singh Talwandi, Shanu Khare and Payal Thakur
12.1 Understanding Healthcare 4.0
12.1.1 Definition and Overview of Healthcare 4.0
12.1.2 Evolution from Traditional Healthcare Models to Healthcare 4.0
12.2 Digital Transformation in Healthcare
12.2.1 The Role of Digital Technologies in Transforming Healthcare Delivery
12.2.2 Benefits and Advantages of Digital Transformation in Patient Care
12.3 Leveraging Artificial Intelligence (AI) in Patient Care
12.3.1 Applications of AI in Diagnostics and Treatment Planning
12.3.2 AI-Driven Personalized Medicine and Predictive Analytics
12.4 Internet of Things (IoT) in Healthcare
12.4.1 Connected Medical Devices and Wearable Technology
12.4.2 Remote Patient Monitoring and Real-Time Health Data Collection
12.5 Big Data Analytics for Healthcare Improvement
12.5.1 Utilizing Healthcare Data for Population Health Management
12.5.2 Predictive Analytics for Disease Prevention and Early Intervention
12.6 Telemedicine and Remote Care Services
12.6.1 Advantages of Telemedicine in Expanding Access to Healthcare Services
12.6.2 Remote Consultations and Virtual Care Delivery Models
12.7 Cybersecurity and Data Privacy in Healthcare 4.0
12.7.1 Challenges and Risks Associated with Digital Transformation in Healthcare
12.7.2 Importance of Cybersecurity Measures to Protect Patient Data
12.8 Conclusion
References
About the Editors
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