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.
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 AI’s 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.
Table of Contents
Preface xxi
1 Smart Aging: Harnessing Artificial Intelligence in Elderly Healthcare 1
S.C. Vetrivel, V. Sabareeshwari, Ramya Ambikapathi, V.P. Arun and K.C. Sowmiya
1.1 Introduction 2
1.1.1 Overview of AI Applications in Healthcare 2
1.1.2 Importance of AI in Addressing Healthcare Challenges for the Elderly 3
1.2 Demographics and Aging Population 3
1.2.1 Statistics on the Aging Population 3
1.2.2 Healthcare Implications and Challenges of an Aging Society 5
1.3 Healthcare Needs of the Elderly 6
1.3.1 Common Health Issues Among the Elderly 6
1.3.2 Unique Challenges in Providing Healthcare for Seniors 8
1.4 Current Healthcare Technologies for the Elderly 9
1.4.1 Overview of Existing Healthcare Technologies 9
1.4.2 Limitations and Gaps in Current Solutions 10
1.5 AI in Diagnostics and Early Detection 12
1.5.1 Use of AI for Early Detection of Diseases 12
1.5.2 Diagnostic Applications in Geriatric Medicine 13
1.6 Remote Monitoring and Telehealth 14
1.6.1 AI-Enabled Remote Monitoring for the Elderly 14
1.6.2 Telehealth Solutions and Their Impact on Elderly Care 16
1.7 Personalized Medicine for the Elderly 17
1.7.1 Tailoring Healthcare Interventions Based on Individual Characteristics 17
1.7.2 AI Applications in Personalized Treatment Plans 17
1.8 Cognitive Assistance and Mental Health 18
1.8.1 AI Solutions for Cognitive Assistance 18
1.8.2 Addressing Mental Health Challenges in the Elderly through AI 19
1.9 Ethical Considerations and Privacy Issues 21
1.9.1 Ethical Challenges in Implementing AI in Healthcare 21
1.9.2 Ensuring Privacy and Security in AI-Powered Healthcare for the Elderly 22
1.10 Integration of AI into Healthcare Systems 22
1.10.1 Challenges and Opportunities in Integrating AI into Existing Healthcare Infrastructure 22
1.10.2 Strategies for Successful Implementation 25
1.11 Future Trends and Innovations 26
1.11.1 Emerging Technologies in AI for Elderly Healthcare 26
1.12 Conclusion 27
References 27
2 Telehealth Use Among Older Adults During COVID 19 33
Ramkrishna Mondal
2.1 Introduction 34
2.2 Telehealth in Geriatrics 36
2.2.1 Patient Safety 36
2.2.1.1 Care Coordination 36
2.2.1.2 Fall Prevention and Home Safety 36
2.2.1.3 Medication Review 37
2.2.2 Remote Health Assessment 37
2.2.2.1 Functional Status 37
2.2.2.2 Frailty 38
2.2.2.3 Nutritional Status 38
2.2.2.4 Medicare Annual Wellness Visit 38
2.2.3 Chronic Disease Management 39
2.2.3.1 Dementia 39
2.2.3.2 Depression 39
2.2.3.3 Heart Failure (HF) 39
2.2.3.4 Diabetes Mellitus 39
2.2.3.5 Hypertension 40
2.3 Role of Telehealth During the COVID Pandemic for the Elderly 41
2.3.1 Telehealth SWOT Analysis 42
2.3.2 Implementation of Telehealth Use for Geriatrics 44
2.3.2.1 The COVID-19 Pandemic Has Significantly Impacted the Availability, Accessibility, Affordability, and Quality of Telehealth in Geriatric Care 45
2.3.2.2 Advantages, Disadvantages, Opportunities, and Threats of Telehealth Use in COVID-19-Related Geriatric Care 45
2.3.2.3 Consequences for Practice and Research Gaps 45
2.3.3 Telemedicine in the International Context and Its Use among Older Adults 45
2.3.4 Use of Telemedicine to Meet Healthcare Needs of Older Adults 46
2.3.4.1 Occupational Assessment 47
2.3.4.2 Occupational Intervention 47
2.3.4.3 Rehabilitation Counseling 47
2.3.4.4 Support for Caregivers 47
2.3.4.5 Activity Monitoring 48
2.4 Factor Affecting Utilization of Telehealth in the Elderly during COVID- 19 48
2.4.1 Factor Affecting Utilization and Access 48
2.4.1.1 Access to COVID-Related Services 49
2.4.1.2 Access to Non-COVID-Related Services 49
2.4.1.3 Literacy and Education 49
2.4.1.4 Perceived Attitudes of Aging 49
2.4.1.5 Accommodation Challenges 49
2.4.1.6 Policies and Structures 50
2.4.1.7 Socio-Cultural 50
2.4.2 Factor Affecting Behavioral Intention 50
2.4.2.1 Theme: Facilitating Conditions 51
2.4.2.2 Theme: Performance Expectancy 51
2.4.2.3 Theme: Effort Expectancy 51
2.4.2.4 Theme: Social Influence 51
2.5 Experiences of Telehealth in the Elderly 52
2.5.1 Experiences in Elderly 52
2.5.1.1 Silver Linings During the Pandemic 53
2.5.1.2 Some Roadblocks to Success 53
2.5.2 Literature Review on Experiences 54
2.5.3 Key Messages Derived from the Literature 55
2.5.4 Telehealth Interventions 56
2.5.4.1 TCC Smartphone-Based Care Model 56
2.5.4.2 Mobile Integrated Health 56
2.5.4.3 HCWs 56
2.5.5 Various Other Countries’ Experiences 57
2.6 Perception of Telehealth Among Elderly and Physicians 58
2.7 Challenges and Barriers of Telehealth for the Elderly 60
2.7.1 Challenges of Telehealth for Elderly 61
2.7.1.1 E-Health Services 61
2.7.1.2 Access to Necessary Resources During Self-Isolation 61
2.7.1.3 A Portion of the Canadian Government’s Support in COVID- 19 61
2.7.1.4 Long-Term Care Facilities (LTCFs) 62
2.7.1.5 Consequences of Self-Isolation on the Body and Mind 62
2.7.1.6 Neglect of Older Individuals, Ageism, and Age Discrimination 62
2.7.2 Barriers to Telehealth 62
2.7.2.1 Patient Barriers 63
2.7.2.2 Clinician Barriers 63
2.7.2.3 Structural and Social Determinants of Health Barriers 63
2.7.2.4 Caregivers 64
2.7.2.5 User-Centered Design in the Development of Telehealth Products 64
2.7.2.6 Structural and Organizational Strategies 64
2.7.3 Overcoming Barriers to Telemedicine Care 64
2.7.3.1 User-Specific Considerations 65
2.7.3.2 Technology-Specific Considerations 65
2.7.3.3 Financial Impact and Reimbursement Policies 65
2.7.3.4 Telemedicine Using Solely Audio 66
2.7.3.5 Extension of Services Added During the Pandemic 66
2.8 Future Direction and Lesson Learned 67
2.9 Conclusion 68
References 70
3 IoT for Seniors: How Technology Improves Quality of Life of Older Adults 105
Jyoti Agarwal, Wazih Ahmad, Imtiyazul Haq, Anu Saxena and T. Gopi Krishna
3.1 Introduction to IoT for Seniors 106
3.1.1 Understanding IoT 106
3.1.2 Relevance of IoT for Seniors 106
3.2 Smart Home Devices for Seniors 108
3.2.1 Smart Thermostat 109
3.2.2 Smart Lighting 109
3.2.3 Voice-Activated Assistants 110
3.3 Health and Wellness Monitoring 111
3.3.1 Wearable Devices 112
3.3.2 Health Tracking Apps 112
3.3.3 Remote Health Monitoring System 112
3.4 Security and Safety of Seniors 113
3.4.1 Telemedicine and Remote Consultation 116
3.4.2 Medication Management System 117
3.4.3 IoT in Assisted Living Facilities 117
3.5 Social Connectivity through IoT 118
3.5.1 Video Calling and Social Apps 119
3.5.2 Online Communities for Seniors 119
3.6 Adapting Existing Devices for Seniors 120
3.6.1 Making Standard Devices Senior-Friendly 120
3.6.2 Accessibility Features in IoT Devices 121
3.6.3 Privacy Measures for Seniors 122
3.6.4 Educating Seniors on Security 123
3.7 Overcoming Technological Barriers 124
3.7.1 Simplifying User Interfaces 124
3.7.2 Providing Tech Support for Seniors 125
3.8 Future Trends in IoT for Seniors 126
3.8.1 An Architectural Framework for Elderly Health Monitoring 128
3.9 Conclusion 130
References 131
4 AI and Robotics in Elderly Personal Assistance: Fostering Independent Living 135
Divya Udayan J. and Umashankar Subramaniam
4.1 Introduction 136
4.2 Personalization in Elderly Healthcare 137
4.2.1 Requirements for Personalized Assistance in Elderly Care 141
4.2.2 Customization Standards for Personalization 142
4.3 Design of an Adaptive Real-Time Intervention System for Elderly in Ambient Assisted Living 142
4.3.1 Visual Perception and Self-Localization 144
4.3.2 Context Awareness and Personalization 145
4.3.2.1 Context-Aware Multi-User Activity Recognition 146
4.3.2.2 Active Learning-Based Multi-User Activity Recognition 147
4.3.3 Activity Analysis and Risk Detection 149
4.3.3.1 Human Activity Recognition (HAR) 150
4.3.3.2 Behavioral Patterns Analysis 151
4.3.3.3 Personalized Assistance 152
4.3.4 Response Actions as Personalized Assistance 155
4.3.4.1 Inter-Module Communication 156
4.4 Effectiveness of Social Robots in Improving Independence of Elderly 158
4.4.1 Real-Time Examples: Socially Assistive Robots in Promoting Personalization 160
4.4.1.1 Effectiveness in Enhancing Independence 160
4.4.1.2 Personalization for Optimized Care 161
4.5 Conclusion 163
References 164
5 Enabling Independence of Elderly People Using IoT Technology 169
Raghav Pasrija, Sandeep Banerjee, Sandeep Sharma and Viktória Schneider
5.1 Introduction 170
5.2 Comprehending IoT: Development and Omnipresence 171
5.2.1 Evolution of IoT Throughout History 171
5.2.2 The Widespread Presence of IoT in Modern Society 171
5.3 Challenges Encountered by Elderly Individuals 173
5.3.1 Physical Health Challenges 173
5.3.2 Challenges Related to Cognition and Mental Health 173
5.3.3 Economic and Societal Obstacles 174
5.4 Constraints of Conventional Approaches 174
5.4.1 Facilities for Institutional Care 174
5.4.2 Home Care Services 175
5.4.3 Challenges in the Healthcare System 175
5.4.4 Cultural and Linguistic Obstacles 176
5.5 Incorporating Internet of Things Technology into Elderly Care 177
5.6 Advancement and Future Research 182
5.7 Summary and Future Prospects 185
5.7.1 Key Findings Summary 185
5.7.2 Prospective Avenues 186
5.8 Conclusion 187
References 187
6 Intersection of AI Tools and Application for Elderly Healthcare 191
Priyanka Suyal, Camellia Chakraborty, Kamal Kumar Gola, Mridula, Pavel Skrabanek, Sagar Gulati and Rajdeep Jung
6.1 Introduction to the Health Tech Landscape 192
6.1.1 Overview of AI and Emerging Technologies 193
6.1.2 AI in Healthcare Applications 193
6.2 AI-Driven Diagnostics, Imaging and Robotics 195
6.2.1 Importance of Medical Imaging in Diagnosing Age-Related Diseases 195
6.2.2 Advancements in Medical Imaging through Artificial Intelligence 196
6.2.3 Robotics in Surgery and Beyond for Elderly 197
6.2.4 Exoskeletons: Empowering Mobility for Elderly 197
6.3 Remote Healthcare Solutions for Elderly Well-Being 198
6.3.1 Telehealth and Remote Patient Monitoring (RPM) 199
6.3.2 Remote Monitoring and AI Predictive Analytics for Elderly 200
6.3.3 Mental Health Support and Social Interaction for the Elderly 201
6.4 Wearable Health Devices and Medication Management for the Elderly 202
6.4.1 Wearable Devices 202
6.4.2 Advances in Smart Devices for Symptom Monitoring 202
6.4.3 Intelligent Medication Management Systems 205
6.4.3.1 Compensation Strategies 205
6.4.3.2 Technology-Mediated Strategies 205
6.5 AI-Based Pain Management Strategies for Elderly Patients 207
6.5.1 Enhanced Pain Assessment Capabilities 208
6.5.2 Predictive Analytics and Clinical Decision Support 208
6.5.3 Empowering Self-Management through Digital Interventions 208
6.6 Future Directions and Ethical Considerations in AI-Driven Elderly Healthcare 209
6.6.1 Key Areas of Potential and Future Trends 209
6.6.2 Challenges and Considerations 209
6.6.3 Ethical Considerations 211
6.6.3.1 Concerns Regarding Beneficence 211
6.6.3.2 Challenges Related to Respect for Autonomy 211
6.6.3.3 Issues Surrounding Justice 212
6.6.3.4 Privacy and Confidentiality 212
6.6.3.5 Transparency and Accountability 212
6.7 Medicare Cataloging Based on AI Technology 213
6.8 Conclusion 215
References 215
7 Technological Impact on Nutrition Management of Adults 219
S.C. Vetrivel, V. Sabareeshwari, Ramya Ambikapathi, V.P. Arun and K.C. Sowmiya
7.1 Introduction 220
7.1.1 Intersection of Technology and Nutrition 220
7.1.2 Historical Perspective on the Evolution of Technology in Nutrition Management 221
7.2 Emerging Technologies in Food Production 222
7.2.1 Genetic Engineering and Its Impact on Food Quality 222
7.2.2 Precision Agriculture and Sustainable Farming Practices 224
7.2.3 Objectives 225
7.3 Digital Health and Nutrition Tracking Apps 226
7.3.1 Overview of Popular Nutrition Tracking Apps 226
7.3.2 Benefits and Limitations of Digital Tracking for Dietary Management 227
7.4 Smart Kitchen Appliances and Gadgets 229
7.4.1 Integration of Technology in Cooking and Meal Preparation 229
7.4.2 Smart Kitchen Devices for Portion Control and Healthy Cooking 230
7.5 Nutrigenomics and Personalized Nutrition 231
7.5.1 Understanding the Role of Genetics in Nutrition 231
7.5.2 Personalized Nutrition Plans Based on Genetic Information 233
7.6 Telehealth and Remote Nutrition Counseling 234
7.6.1 Remote Access to Nutrition Experts through Technology 234
7.6.2 Virtual Consultations and Monitoring for Dietary Management 235
7.7 Wearable Technology for Fitness and Nutrition 236
7.7.1 Fitness Trackers and Their Impact on Physical Activity and Diet 236
7.7.2 Smart Wearables for Real-Time Health Monitoring 237
7.8 Augmented Reality in Nutrition Education 238
7.8.1 AR Applications for Nutrition Education and Awareness 238
7.8.2 Interactive Experiences for Learning About Food Choices and Portion Control 239
7.9 Blockchain in the Food Supply Chain 240
7.9.1 Ensuring Transparency and Traceability in the Food Supply 240
7.9.2 Reducing Food Fraud and Improving Food Safety through Blockchain 241
7.10 Challenges and Ethical Considerations 242
7.10.1 Addressing Privacy Concerns in Health and Nutrition Technology 242
7.10.2 Ethical Considerations in the Use of Emerging Technologies 243
7.11 Future Trends in Technological Nutrition Management 244
7.11.1 Predicting Future Developments in Technology and Nutrition 244
7.11.2 Potential Breakthroughs and Their Impact on Adult Nutrition 245
7.12 Conclusion 246
References 247
8 Empowering Nutrition and Diet of Elderly People Using Digital Technology 251
Shiva Tushir, Navidha Aggarwal, Himanshu Sehrawat and Sabina Yasmin
8.1 Understanding Nutrition 252
8.1.1 Definition of Nutrition 252
8.1.2 Macronutrients and Micronutrients 253
8.2 Various Types of Macronutrients and Micronutrients 253
8.2.1 Proteins 253
8.2.2 Carbohydrates 254
8.2.3 Fats 254
8.2.4 Micronutrients 254
8.2.5 Vitamins and Minerals 254
8.2.6 Hydration 255
8.2.7 Phytonutrients 255
8.2.8 Water and Hydration 256
8.3 Nutrient Absorption and Metabolism 256
8.3.1 Enhancement of Bioavailability 256
8.3.2 Nutrition Tracking and Smartphone Applications 256
8.3.3 Nutraceuticals and Functional Foods 257
8.3.4 Gut Microbiota and Nutrition Utilization 257
8.3.5 Artificial Intelligence in Nutrition Analysis 257
8.3.6 Medical Technologies for Nutrient Administration 257
8.4 Key Concepts and Terminology Related to Nutrition 258
8.4.1 Concepts of Nutrition 258
8.4.2 Nutritional Concept 258
8.4.3 Nutrition for Clinical Practice 259
8.4.4 Undernourishment 259
8.4.5 Malnutrition Linked to Disease (DRM) Combined with Inflammation 259
8.4.6 Importance of Nutrition Management 260
8.4.6.1 Disease Prevention and Health Promotion 260
8.4.6.2 Body Composition and Weight Management 261
8.4.6.3 Enhancing Performance and Maintaining Physical Fitness 261
8.4.6.4 Mental Health and Cognitive Function 261
8.5 Fundamentals of Technology 262
8.5.1 Data Gathering and Analysis 262
8.5.2 Nutrition Tracking Apps 262
8.5.3 Diet Plan Apps 262
8.5.4 Nutrition-Related Education 263
8.5.5 Precision Approach of Nutrition 263
8.5.6 Telehealth and Remote Monitoring 263
8.6 Introduction to Technology 263
8.7 Need of Technology for Health 264
8.7.1 Incremental Analysis 264
8.7.2 Accessible Information 264
8.7.3 Filling of Communication Gap 265
8.7.4 Highly Efficient and Cost Effective 265
8.7.5 Personalized Nutrition Approach 265
8.7.6 Public Health Nutrition Concern 265
8.7.7 Preventive Health Care 265
8.7.8 Empowering People with Chronic Issues 266
8.7.9 Closing the Healthcare Access Gap 266
8.8 Technology for Disease Management in COVID- 19 266
8.9 Technological Interventions for Self-Care 268
8.10 Artificial Intelligence 269
8.10.1 Personalized Nutrition Recommendations 269
8.10.2 Nutritional Analysis 270
8.10.3 Nutritional Content Prediction 270
8.10.4 Behavioral Analysis and Coaching 270
8.10.5 Disease Risk Prediction and Prevention 270
8.10.6 Chatbots and Virtual Assistants Driven by Artificial Intelligence 270
8.10.7 Food Supply Chain Optimization 271
8.11 Deep Learning 271
8.11.1 Customized Evaluation of Food Consumption 271
8.11.2 Nutrition Advice and Customized Meal Planning 271
8.11.3 Predicting and Managing Disease Risk 271
8.11.4 Analysis of Food Behavior and Habits 272
8.11.5 Motivational Tools and Gamification 272
8.12 Machine Learning 272
8.12.1 Food and Nutrient Intake Tracking 272
8.12.2 Coaching and Modification of Behavior 272
8.12.3 Customized Food Delivery Services 273
8.12.4 Disease Identification and Prevention 273
8.12.5 Nutritional Profile 274
8.12.6 Gut Health Analysis 274
8.12.7 Health Prediction 274
8.13 Limitations of Machine Learning 274
8.13.1 Model Transparency 274
8.13.2 Accessibility 274
8.13.3 Regulation and Supervision 274
8.13.4 Integration with Other Technologies 275
8.13.5 Emphasis on Behavior Modification 275
8.13.6 Cooperation between Varied Stakeholders 275
8.14 Role of Various Technological Interventions in Self-Care 275
8.15 Possible Advantages 276
8.15.1 Improved Access 276
8.15.2 Active Engaging 276
8.15.3 Data Collection and Health Monitoring 276
8.15.4 Enhanced Health Support 277
8.16 Possible Limitations 277
8.16.1 Digital Gap 277
8.16.2 Privacy 277
8.16.3 Over-Reliance 277
8.16.4 Accessible to Users 277
8.16.5 Misidentification 277
References 278
9 Healthcare 4.0: Healthcare in Technological World 281
Manoj Kumar Mahto, Durgesh Srivastava and Santosh Kumar Srivastava
9.1 Introduction 282
9.1.1 The Silver Tsunami and Its Challenges for Healthcare 282
9.1.2 Healthcare 4.0: A Technological Revolution for Elder Care 283
9.1.3 The Promise of AI, Big Data, and the Internet of Things (IoT) 284
9.2 AI-Powered Tools for Proactive Healthcare and Chronic Disease Management 285
9.2.1 Early Disease Detection and Risk Prediction 286
9.2.2 Personalized Health Education and Support with AI Chatbots 287
9.2.3 Remote Monitoring and Proactive Intervention for Chronic Conditions 288
9.3 Transforming Remote Care with Telehealth and Connected Devices 288
9.3.1 Smart Homes and Wearables for Real-Time Vital Sign Monitoring 289
9.3.2 Telehealth Platforms for Virtual Consultations and Remote Diagnosis 290
9.3.3 AI-Powered Virtual Companions and Social Robots for Combating Loneliness 291
9.4 Personalized Care Plans and Decision Support Systems 291
9.4.1 Tailored Treatment Recommendations and Medication Schedules 292
9.4.2 AI-Driven Decision Support Systems for Healthcare Professionals 293
9.4.3 Ethical Considerations and Transparency in AI-Based Healthcare 293
9.5 Challenges and Opportunities: Ethical Considerations and Future Directions 294
9.5.1 Data Privacy and Security Concerns in Healthcare 4.0 295
9.5.2 Bridging the Digital Divide for Equitable Access to Technology 296
9.5.3 Mitigating Bias and Discrimination in AI-Powered Healthcare 297
9.5.4 Human-Centric Design and the Importance of Patient Autonomy 298
9.6 Conclusion: A Future of Empowered and Accessible Elder Care 299
9.6.1 The Potential of Healthcare 4.0 to Improve Quality of Life and Care Outcomes 300
9.6.2 Fostering Collaboration and Accountable Development of AI in Healthcare 301
9.6.3 A Vision for a Future Where Technology Empowers, Not Replaces, Human Care 301
References 302
10 Ethical Considerations in AI-Powered Nutrition Guidance: Balancing Privacy, Data Security, and Bias Mitigation 305
Shweta Saraswat, Vrishit Saraswat, Kamalkant Jain and Shourya Sharma
10.1 Introduction 306
10.1.1 Background 306
10.1.2 Objectives of AI-Powered Nutrition Guidance 306
10.1.3 Importance of Ethical Considerations 308
10.2 Privacy Concerns in AI-Powered Nutrition Guidance 310
10.2.1 Collection of Personal Data 310
10.2.2 Transparency and Informed Consent 311
10.2.3 Data Ownership 313
10.2.4 Striking the Balance between Personalization and Privacy 315
10.3 Data Security in AI-Powered Nutrition Guidance 317
10.3.1 Ensuring the Protection of Personal and Health Data 317
10.3.2 Encryption Techniques 319
10.3.3 Secure Storage Solutions 321
10.3.4 Periodic Security Audits 323
10.4 Bias Mitigation in AI-Powered Nutrition Guidance 325
10.4.1 Understanding Bias in AI Systems 325
10.4.2 Scrutinizing Data Sources 327
10.4.3 Algorithmic Decision Making 328
10.4.4 Continuous Monitoring and Adjustment 329
10.5 Recommendations and Best Practices 329
10.6 Case Studies 331
10.6.1 Ethical Challenges Faced by Existing AI-Powered Nutrition Platforms 331
10.6.2 Successful Implementation of Ethical Guidelines 333
10.7 Future Perspectives 333
10.7.1 Evolving Ethical Standards 333
10.7.2 Technological Advances in Privacy, Security, and Bias Mitigation 337
10.8 Conclusion 337
References 339
11 Prevention of Blindness for Diabetic Patients Using Deep Learning Techniques 343
U. Sadhana, Beena B.M. and Prashanth C. Ranga
11.1 Introduction 344
11.2 Related Works 346
11.3 Case Studies of Diabetic Retinopathy 348
11.4 Techniques to Detect Diabetic Retinopathy 348
11.5 Deep Learning Methods to Detect Diabetic Retinopathy 351
11.6 Dataset 352
11.7 Results 352
11.8 Conclusion 354
References 355
12 Transitioning to Healthcare 4.0: Embracing Digital Innovation for Enhanced Patient Care and Outcomes 359
Navjot Singh Talwandi, Shanu Khare and Payal Thakur
12.1 Understanding Healthcare 4.0 360
12.1.1 Definition and Overview of Healthcare 4.0 360
12.1.2 Evolution from Traditional Healthcare Models to Healthcare 4.0 362
12.2 Digital Transformation in Healthcare 364
12.2.1 The Role of Digital Technologies in Transforming Healthcare Delivery 364
12.2.2 Benefits and Advantages of Digital Transformation in Patient Care 366
12.3 Leveraging Artificial Intelligence (AI) in Patient Care 367
12.3.1 Applications of AI in Diagnostics and Treatment Planning 367
12.3.2 AI-Driven Personalized Medicine and Predictive Analytics 368
12.4 Internet of Things (IoT) in Healthcare 369
12.4.1 Connected Medical Devices and Wearable Technology 369
12.4.2 Remote Patient Monitoring and Real-Time Health Data Collection 371
12.5 Big Data Analytics for Healthcare Improvement 372
12.5.1 Utilizing Healthcare Data for Population Health Management 372
12.5.2 Predictive Analytics for Disease Prevention and Early Intervention 374
12.6 Telemedicine and Remote Care Services 375
12.6.1 Advantages of Telemedicine in Expanding Access to Healthcare Services 375
12.6.2 Remote Consultations and Virtual Care Delivery Models 377
12.7 Cybersecurity and Data Privacy in Healthcare 4.0 378
12.7.1 Challenges and Risks Associated with Digital Transformation in Healthcare 378
12.7.2 Importance of Cybersecurity Measures to Protect Patient Data 379
12.8 Conclusion 380
References 380
About the Editors 383
Index 387
