Artificial Intelligence-Enabled Blockchain Technology and Digital Twin for Smart Hospitals

Preface xix Part 1: Basic Fundamentals and Principles 1 1 Introduction to Smart Hospital 3 R. Bhuvana, R. J. Hemalatha, S. Baskar and Krishnakumar Kosalaram 1.1 Introduction 4 1.2 Conclusion 14 1.3 Demerits of Smart Hospitals 15 2 Wireless Medical Sensor Networks in Smart Hospitals 19 Renugadevi A. S., Jayaprakash M., Kaviya P., Kavin Raj P.N. and Jenish G.S. 2.1 Introduction 19 2.2 Wireless Sensor Network 21 2.3 Application in Healthcare 24 2.4 Benefits 33 2.5 Technical Challenges 34 2.6 Conclusion 36 3 Introduction of DNA Computing in Cryptography 39 M. Venkata Krishna Reddy, R. Ravinder Reddy, E. Padma Latha, Sirisha Alamanda and P.V.S. Srinivas 3.1 Introduction 39 3.2 Steganography 42 3.3 Related Work on DNA 43 3.4 DNA Computing 45 3.5 Essence of DNA Computing 46 3.6 Role of DNA Computing in Cryptography 47 3.7 Applications of DNA Computing 49 3.8 Related Work on DNA-Based Cryptography (Document) 51 3.9 Limitations 53 3.10 Cryptography Methods Based on DNA 54 3.11 Experimental Analysis 57 3.12 Conclusions and Future Work 58 Part 2: Methods and Applications 61 4 Enhancing Diabetic Retinopathy and Glaucoma Diagnosis through Efficient Retinal Vessel Segmentation and Disease Classification 63 Asadi Srinivasulu 4.1 Introduction 64 4.2 Literature Review 64 4.3 Existing System 65 4.4 Proposed System 66 4.5 Experimental Results 69 4.6 Conclusion 74 5 Machine Learning-Enabled Digital Twins for Diagnostic and Therapeutic Purposes 77 Neel Shah, Jayansh Nagar, Kesha Desai, Nirav Bhatt, Nikita Bhatt and Hiren Mewada 5.1 Introduction 78 5.2 Conceptualization of Digital Twin and Machine Learning 79 5.3 State-of-the-Art Works 87 5.4 Applications of Digital Twins Enabled With Deep Learning Models and Reinforcement Learning 90 5.5 Limitations and Challenges 91 5.6 Opportunities/Future Scope 93 5.7 Concluding Remarks 93 6 Blockchain as the Backbone of a Connected Ecosystem of Smart Hospitals 99 C.M. Nalayini, V. Sathya, Shruthi Arunkumar and M. Dinesh Babu 6.1 Introduction 100 6.2 Smart Hospitals 101 6.3 Foundations of Blockchain Technology 104 6.4 Literature Survey 105 6.5 Integration of Blockchain in Healthcare 108 6.6 Digital Twin Technology in Smart Hospitals 110 6.7 Benefits and Challenges 111 6.8 Building A Connected Ecosystem 113 6.9 Regulatory Considerations 115 6.10 Case Study 117 6.11 Future Trends and Innovation 119 6.12 Conclusion 120 7 Blockchain for Edge Association in Digital Twin Empowered 6G Networks 123 C. Fancy, M. Anand and T. M. Sheeba 7.1 Introduction 123 7.2 Digital Twin Technology 125 7.3 Edge Computing in 6G Networks 127 7.4 The Blockchain Technology 129 7.5 Blockchain, Digital Twin, and Edge Computing Integration 133 7.6 Case Studies from Multiple Domains 139 7.7 Prospects for Future Directions and Research 144 8 Blockchain for Security and Privacy in the Smart Healthcare 153 V. Karthikeyan, S. Sridhar Raj, K. Gopalakrishnan, J. Dani Reagan Vivek and Anita Antwiwaa 8.1 Brief Overview of Medical Records and Their Confidentiality 153 8.2 Basics of Blockchain Technology 157 8.3 Benefits of BC Regarding the Protection of Medical Data 159 8.4 Principles of Using Blockchain for Medical Records 161 8.5 IAM on the Blockchain 162 8.6 Encrypted Medical Information Exchange via Blockchain 163 8.7 Insurance User Intelligence and Power in Blockchain-Enabled Services 165 8.8 Governmental and Moral Thoughts 166 8.9 Selected Experiences and Recommended Approaches 166 8.10 Prospects and Hurdles in Advancing Blockchain-Based Health Record Security 169 8.11 Conclusion and Future Prospects 173 9 Conceptual and Empirical Evidence for the Implementation of Blockchain Technology as a Solution for Healthcare Service Providers in India 179 B.C.M. Patnaik, Ipseeta Satpathy, Rocky Dwyer, Amit Kumar Tyagi and Anish Patnaik 10 Blockchain-Enabled Internet of Things (IoTs) Platforms for IoT-Based Healthcare and Biomedical Sectors 201 Amit Kumar Tyagi 10.1 Introduction 202 10.2 Various Applications of Blockchain and Internet of Things in Healthcare and Biomedical Sectors 203 10.3 Internet of Things Supported Blockchain Platforms in Healthcare and Biomedical Sectors 204 10.4 Blockchain Technology for Healthcare and Biomedical Sectors 205 10.5 Storage Capacity and Scalability for Electronic Health Records (EHR) 206 10.6 Security Issues in Healthcare and Biomedical Sectors: Weaknesses and Threats in Blockchain-Based Internet of Things 207 10.7 Privacy Issues in Healthcare and Biomedical Sectors: Weaknesses and Threats in Blockchain-Based Internet of Things 208 10.8 Trust Issue in Healthcare and Biomedical Sectors: Weaknesses and Threats in Blockchain-Based Internet of Things 209 10.9 Other Issues Healthcare and Biomedical Sectors Rather than Security, Privacy, and Trust 210 10.10 Technical and Non-Technical Challenges in Healthcare and Biomedical Sectors 212 10.11 Future Work Toward Healthcare and Biomedical Sectors 213 10.12 Conclusion 214 11 Electronic Health Records in a Blockchain 219 Reshma V. and Rajesh Mamilla 12 A PSO-Based Hybrid Cardiovascular Disease Prediction for Using Artificial Flora Algorithm 231 Ritu Aggarwal, Gulbir Singh and Eshaan Aggarwal 12.1 Introduction 231 12.2 Literature Review 232 12.3 Proposed Methodology 233 12.4 Machine Learning Algorithms 235 12.5 Experimental Setup 238 12.6 Conclusion 241 13 AI and Transfer Learning-Based Framework for Efficient Classification and Detection of Lyme Disease 245 Pramit Brata Chanda, Saikat Das, Sharanya Bhattacharya, Souhardya Biswas and Subir Kumar Sarkar 13.1 Introduction 246 13.2 Literature Survey 247 13.3 Methodologies 249 13.4 Proposed Work 254 13.5 Results and Analysis 260 13.6 Conclusion 264 14 Framework for Gender Detection Using Facial Countenances 269 Shyla, Shalu and Mohit Dayal 14.1 Introduction 269 14.2 Objectives 271 14.3 Methodology 273 14.4 Architecture 276 14.5 Raining and Evaluation 279 14.6 Conclusion 283 Part 3: Issues and Challenges 287 15 Unveiling the Challenges and Limitations in COVID-19 Health Data Prediction with Convolutional Neural Networks: A Data Science Research Perspective 289 Asadi Srinivasulu, Piyush Agrawal, Amit Agrawal and Goddindla Sreenivasulu 15.1 Introduction 289 15.2 Literature Review 291 15.3 Methodology 293 15.4 Challenges in COVID-19 Health Data Prediction 295 15.5 Limitations of Convolutional Neural Networks 298 15.6 Mitigation Strategies 299 15.7 Case Study: An Empirical Analysis of CNNs for COVID-19 Health Data Prediction 301 15.8 Conclusion 305 Part 4: Future Opportunities 309 16 Cloud-Based Digital Twinning for Structural Health Monitoring Using Deep Learning 311 K. Renugadevi, T. Jayasankar and J. ArputhaVijaya Selvi 16.1 Introduction to Cloud-Based Digital Twinning 312 16.2 Evolution of Structural Health Monitoring (SHM) 312 16.3 Digital Twinning: Concept and Applications 313 16.4 Integration of Cloud Computing in SHM 315 16.5 Deep Learning Techniques for Sensor Data Analysis 316 16.6 Leveraging Convolutional Neural Networks (CNNs) in Cloud Environment 318 16.7 Recurrent Neural Networks (RNNs) for Anomaly Detection 319 16.8 Proactive Maintenance and Early Fault Detection 319 16.9 Collaboration and Data Sharing in Cloud-Based Deployment 320 16.10 Anticipated Outcomes and Implications 321 16.11 Advancing SHM Technologies with Cloud-Based Solutions 322 16.12 Promoting Resilience and Sustainability through Intelligent SHM Systems 323 16.13 Conclusion 324 17 Smartphone-Based Sensors for Biomedical Applications 327 Amit Kumar Tyagi, Richa and Shabnam Kumari 17.1 Introduction to Smartphone-Based Sensors and Its Importance in Biomedical Applications 328 17.2 Smartphone-Based Sensors for Biomedical Applications 332 17.3 Benefits, Limitations, Issues, and Challenges of Smartphone-Based Sensors in Biomedical Application 333 17.4 Ensuring Data Security and Privacy in Biomedical Applications by Using Smartphone-Based Sensors 336 17.5 Sensor Technologies and Communication Protocols in Biomedical Applications 338 17.6 Data Processing and Analysis Using Emerging Technologies in Biomedical Applications 339 17.7 Future Research Directions in Biomedical Sensing Using Smartphone-Based Sensors 341 17.8 Conclusion 343 18 Blockchain for Improving Security and Privacy in the Smart Sensor Network 347 Amit Kumar Tyagi and Tanuj Surve 18.1 Introduction to Smart Sensor Networks and Blockchain Technology 348 18.2 Blockchain for Improving Security and Privacy in the Smart Sensor Network 356 18.3 Real-World Examples of Blockchain in Smart Sensor Networks 359 18.4 Issues and Challenges with Recommended Solutions of Using Blockchain in the Smart Sensor Network for Improving Security and Privacy in this Smart Era 360 18.5 Future Opportunities with Emerging Technologies in Blockchain for Smart Sensor Networks 361 18.6 Potential Advancements in Security and Privacy Using Emerging Technologies for Smart Sensor Networks 363 18.7 Incorporating Blockchain in Existing Sensor Networks for Better Efficiency 364 18.8 Conclusion 366 19 Sensors and Digital Twin Application in Healthcare Facilities Management 369 Amit Kumar Tyagi 19.1 Introduction to Healthcare Facilities Management 369 19.2 Digital Twins: Concepts and Applications 373 19.3 Facilities Management with Digital Twins for Effective Healthcare Facilities 376 19.4 Benefits and Disadvantages of Emerging Technologies in Modern Healthcare Facilities 377 19.5 Security and Privacy Issues in Modern Healthcare Facilities 379 19.6 Data Security in Healthcare Facilities 381 19.7 Real-World Examples of Sensor and Digital Twin Implementation/Solution for Better Healthcare Facilities Management 383 19.8 Challenges and Recommended Solutions for Better Healthcare Facilities Management 385 19.9 Future Trends and Innovations Toward Better Healthcare Facilities Management 386 19.9.1 The Future of Digital Twins in Healthcare 387 19.10 Conclusion 388 20 Integration of Internet of Medical Things (IoMT) with Blockchain Technology to Improve Security and Privacy 391 Silky Pareyani, Neeta Nathani and Jagdeesh Kumar Ahirwar 20.1 Introduction 392 20.2 Motivation 394 20.3 Background 394 20.4 State of the Art 402 20.5 Technical Challenges 403 20.6 Significant Future Trends of Blockchain in Healthcare 406 20.7 Conclusion 407 21 Advancing Healthcare Diagnostics: Machine Learning-Driven Digital Twins for Precise Brain Tumor and Breast Cancer Assessment 413 J. Olalekan Awujoola, T. Aniemeka Enem, F. N. Ogwueleka, O. Abioye and E. Abidemi Awujoola 21.1 Introduction 414 21.2 Digital Twin 416 21.3 The Contribution of Machine Learning and Deep Learning to the Advancement of Digital Twins in Healthcare 418 21.4 Machine Learning in Cancer and Brain Prediction 419 21.5 Materials and Methods 423 21.6 Experimental Results and Analysis 425 21.7 Conclusion and Recommendation 430 22 Digital Twin Applications in Healthcare Facilities Management 435 Kandan M., Naveen P., G. Nagarajan and S. Janagiraman 22.1 Introduction to Digital Twin Technology in Healthcare 436 22.2 Adoption of Digital Twins in Healthcare Facility Management 436 22.3 Evolution from Engineering and Manufacturing to Healthcare 437 22.4 Real-Time Virtual Duplicates for Facility Management 438 22.5 Features of Digital Twins: Sensors, Data Analytics, and Simulation 440 22.6 Challenges in Healthcare Facility Management 440 22.7 Resource Allocation and Patient Safety 442 22.8 Operational Efficiency in Healthcare Facilities 443 22.9 Monitoring Infrastructure, Equipment, and Patient Movement 444 22.10 Integration of Sensor Data EHRs, and Other Sources 445 22.11 Empowering Stakeholders with Insights from Digital Twins 445 22.12 Continuous Improvement and Adaptive Management in Healthcare 446 22.13 Conclusion 447 23 Ethical and Technological Convergence: AI and Blockchain in Halal Healthcare 451 Md Mahfujur Rahman 23.1 Introduction 451 23.2 Balancing Ethics and Faith: AI and Blockchain in Halal Healthcare 453 23.3 AI-Driven Halal Healthcare: Navigating Compliance and Technological Integration 456 23.4 Streamlining Halal Healthcare via Blockchain 459 23.5 AI and Blockchain in Halal Healthcare: Regulatory Frontiers 462 23.6 Conclusion 463 Acknowledgment 464 References 464 Index 467