5.6.4 Algorithm for Distributed Healthcare Using Blockchain 108
5.7 Security for Healthcare System Using Blockchain 109
5.7.1 Framework for Security Using Blockchain 110
5.8 Issues and Challenges in Healthcare Using Blockchain 112
5.9 Future Scope 114
5.10 Conclusion 115
References 115
6 Industry 4.0 and Smart Healthcare: An Application Perspective 117 R. Saminathan, S. Saravanan and P. Anbalagan
6.1 Introduction 118
6.2 Evolution of Industry 4.0 119
6.3 Vision and Challenges of Industry 4.0 120
6.4 Technologies Used in Fourth Industrial Revolution 121
6.5 Blockchain in Industry 4.0 127
6.6 Smart Healthcare Design Using Healthcare 4.0 Processes 129
6.7 Blockchain Tele-Surgery Framework for Healthcare 4.0 131
6.8 Digital Twin Technology in Healthcare Industry 133
6.9 Conclusion 134
References 134
7 Blockchain Powered EHR in Pharmaceutical Industry 137 Piyush Sexena, Prashant Singh, John A. and Rajesh E.
7.1 Introduction 138
7.2 Traditional Healthcare System vs Blockchain EHR 140
7.3 Working of Blockchain in EHR 141
7.4 System Design and Architecture of EHR 143
7.5 Blockchain Methodologies for EHR 146
7.6 Benefits of Using Blockchain in EHR 149
7.7 Challenges Faced by Blockchain in HER 151
7.8 Future Scope 154
7.9 Conclusion 155
References 156
8 Convergence of IoT and Blockchain in Healthcare 159 Swaroop S. Sonone, Kapil Parihar, Mahipal Singh Sankhla, Rajeev Kumar and Rohit Kumar Verma
8.1 Introduction 160
8.2 Overview of Convergence 161
8.3 Healthcare 162
8.4 IoTs and Blockchain Technology 163
8.5 IoT Technologies for Healthcare 163
8.6 Blockchain in Healthcare 165
8.7 Integration for Next-Generation Healthcare 167
8.8 Basic Structure of Convergence 170
8.9 Challenges 172
8.10 Conclusion 174
References 175
9 Disease Prediction Using Machine Learning for Healthcare 181 S. Vijayalakshmi and Ashutosh Upadhyay
9.1 Introduction to Disease Prediction 182
9.1.1 Artificial Intelligence in Healthcare 182
9.1.2 Data Collection and Information Processing 183
9.1.3 Human Living Standard and Possible Diseases 185
9.1.4 Importance of Data in Disease Prediction 185
9.2 Data Analytics for Disease Prediction 186
9.3 Segmentation and Features of Medical Images 186
9.4 Prediction Model for Healthcare 188
9.5 Introduction to ML 191
9.5.1 K-Nearest Neighbor, Artificial Neural Network, CNN, Decision Tree, and Random Forest 195
9.6 Prediction Model Study of Different Disease 198
9.7 Decision Support System 199
9.8 Preventive Measures Based on Predicted Results 199
9.9 Conclusions and Future Scope 200
References 200
10 Managing Healthcare Data Using Machine Learning and Blockchain Technology 203 BKSP Kumar Raju Alluri
10.1 Introduction 203
10.2 Current Situation of Healthcare 204
10.3 Introduction to Blockchain for Healthcare 206
10.4 Introduction to ML for Healthcare 211
10.4.1 Open Issues in Machine Learning for Healthcare 213
10.5 Using ML and Blockchain for Healthcare Management 214
10.5.1 Bucket 1: Theory Centric 215
10.5.2 Bucket 2: Result Oriented 219
10.5.3 Outcomes of the Study 222
10.5.4 Why are Most of the Current Blockchain + Healthcare Papers Theory-Based? 227
10.6 Conclusion 228
References 228
11 Advancement of Deep Learning and Blockchain Technology in Health Informatics 235 Anubhav Singh, Mahipal Singh Sankhla, Kapil Parihar and Rajeev Kumar
11.1 Introduction 236
11.2 Associated Works 238
11.2.1 Preliminaries 240
11.3 Internet of Things 240
11.4 Big Data 241
11.5 Deep Learning 241
11.5.1 Common Deep Learners 242
11.5.1.1 Convolutional Neural Network 242
11.5.1.2 Recurrent Neural Networks 242
11.5.1.3 Deep Autoencoders 243
11.5.1.4 Deep Boltzmann Machine 243
11.6 Restricted Boltzmann Machine 243
11.7 Profound Conviction Organization 244
11.8 Application and Challenges of Deep Learners 244
11.8.1 Predictive Healthcare 244
11.8.2 Medical Decision Support 245
11.8.3 Personalized Treatments 245
11.8.4 Difficulties 246
11.8.5 Blockchain Technology 247
11.8.6 Types of Blockchain 247
11.8.7 Challenges of Blockchain in Healthcare 248
11.8.8 Interoperability 248
11.8.9 Management, Privacy, and Anonymity of Data 248
11.8.10 Quality of Service 249
11.8.11 Heterogeneous Gadgets and Traffic 249
11.8.12 Inertness 249
11.8.13 Asset Imperatives and Energy Proficiency 249
11.8.14 Storage Capacity and Scalability 250
11.8.15 Security 250
11.8.16 Data Mining 250
11.8.17 System Model 251
11.8.18 Attack Model 251
11.9 Open Research Issues 252
11.10 Conclusion 252
References 253
12 Research Challenges and Future Directions in Applying Blockchain Technology in the Healthcare Domain 257 Sneha Chakraverty and Sakshi Bansal
12.1 Introduction 258
12.2 Healthcare 259
12.2.1 Stakeholders of Indian Healthcare Ecosystem 259
12.2.2 Major Data Related Challenges in Indian Healthcare System 260
12.3 Need of Blockchain in Healthcare Domain 261
12.4 Application of Blockchain in Healthcare Domain 262
12.5 Methodology 263
12.5.1 Review of Literature 264
12.5.2 Interviews 264
12.6 Challenges 265
12.6.1 How to Overcome This Problem 267
12.7 Future Directions 268
12.8 Conclusion 269
References 269
Appendix 272
Appendix 12.1 272
Interview Form 272
Appendix 12.2: Response 1 273
Interview Form 273
Appendix 12.3: Response 2 276
Interview Form 276
Appendix 12.4: Response 3 278
Interview Form 278
Appendix 12.5: Response 4 280
Interview Form 280
Index 285
The book gives a detailed description of the integration of blockchain technology for Electronic Health Records and provides the research challenges to consider in various disciplines such as supply chain, drug discovery, and data management.
The aim of the book is to investigate the concepts of blockchain technology and its association with the recent development and advancements in the medical field. Moreover, it focuses on the integration of workflow strategies like NLP, and AI which could be adopted for boosting the clinical documentation and electronic healthcare records (EHR) usage by bringing down the physician EHR data entry. Also, the book covers the usage of smart contracts for securing patient records. Digitization of Healthcare Data Using Blockchain presents the practical implementations that deal with developing a web framework for building highly usable healthcare applications, a simple blockchain-powered EHR system.
About the Author
T. Poongodi, PhD, is an associate professor in the Department of Computer Science and Engineering at Galgotias University, Delhi – NCR, India. She has more than 15 years of experience working in teaching and research.
D. Sumathi, PhD, is an associate professor at VIT-AP University, Andhra Pradesh. She has an overall experience of 21 years out of which six years in industry, 15 years in the teaching field. Her research interests include cloud computing, network security, data mining, natural language processing, and theoretical foundations of computer science.
B. Balamurugan, PhD, is a professor in the School of Computing Sciences and Engineering at Galgotias University, Greater Noida, India. His contributions focus on engineering education, blockchain, and data sciences. He has published more than 30 books on various technologies and more than 150 research articles in SCI journals, conferences, and book chapters.
K. S. Savita, PhD, is on the academic staff in the Department of Computer and Information Sciences (CISD), Universiti Teknologi PETRONAS (UTP), Malaysia since 2006. She is accredited by the Malaysia Board of Technologies as Professional Technologist (Ts.) in Information and Computing Technology.