Preface xv 1 Introduction to Algorithmic Health: Exploring Healthcare Through Digital Twins 1A.S. Vinay Raj, N. Gopinath, R. Anandh, M. Mohammed Jalaluddin and Lyndsay R. Buckingham 1.1 Introduction 2 1.2 Related Works 3 1.3 Hardware Description 6 1.4 Methodology 12 1.5 Performance Analysis 21 1.6 Conclusion 22 2 The Digital Revolution in Healthcare 27Devanand Bhonsle, Rama Shukla, Deepshikha Sahu, Tanuja Kashyap, Monika Dewangan and Seema Mishra 2.1 Introduction 27 2.2 Digital Technologies in the Healthcare Sector 30 2.3 Evolution of Digitalization in Business 31 2.4 Role of IoMT in Healthcare 33 2.5 Internet of Medical Things Devices 35 2.6 Security and Privacy in the Healthcare Sector 36 2.7 Eliminating Security and Privacy Concerns of Digitalization of the Healthcare Sector 37 2.8 Discussion 39 2.9 Future Works 39 2.10 Conclusion 41 3 Data-Driven Diagnostics: Deep Learning for Brain Tumor Classification 45Astha Pathak and Lalita Panika 3.1 Introduction 45 3.2 Literature Review 47 3.3 Methodology 52 3.4 Result Analysis 55 3.5 Conclusion 57 4 Predictive Analysis in Patient Care 61Bolukonda Prashanth, Bandi Krishna, Rakesh Nayak, Umashankar Ghugar and Arunakranthi Godishala 4.1 Introduction 62 4.2 Review of Predictive Analysis 68 4.3 Conclusion and Future 80 5 Leveraging Predictive Analytics: Enhancing Brain Tumor Classification with XGBoost 85Katakam Hemanvitha and Vikram Dhiman 5.1 Introduction 86 5.2 Literature Review 87 5.3 Methodology 93 5.4 Results and Discussion 97 5.5 Conclusion 100 6 Machine Learning in Medical Imaging Revolutionizing Lung Cancer Diagnosis: A Comparative Analysis of Convolutional Neural Networks and Vision Transformers in Medical Imaging 103Priya Parkhi, Bhagyashree Hambarde, Himesh Gangwani, Rupali Vairagade and Fred Kalombo 6.1 Introduction 104 6.2 Literature Review 108 6.3 Description of Model 110 6.4 Methodology 113 6.5 Results 118 6.6 Conclusion 124 7 Innovations in AI and ML for Medical Imaging: An Extensive Study with an Emphasis on Face Spoofing Detection and Snooping 127Aparna Pandey, Arvind Kumar Tiwari, Harsha Nishad and Siji A. Thomas 7.1 Introduction 128 7.2 Artificial Intelligence as Well as Device Understandings 132 7.3 Assaults Through Entrance Spoofing 138 7.4 A Case Study with Real-Time Narrative: Identifying Face Spoofing in Medical Imaging 144 7.5 Moral Factors to Consider 146 7.6 Discussion 149 7.7 Summary 150 8 Progressive Growing of Generative Adversarial Networks (PGGAN) Approach to Synthesize Medical Images 157Vishal V. Raner, Amit D. Joshi, Suraj T. Sawant and Tamizharasan P. S. 8.1 Introduction 158 8.2 Literature Review 160 8.3 Methodology 162 8.4 Results and Discussion 167 8.5 Conclusions 173 9 Revolutionizing Healthcare Through Optimized Video Retrieval 177Pratibha Singh and Alok Kumar Singh Kushwaha 9.1 Introduction 178 9.2 Literature Review 180 9.3 Methodology 182 9.4 Results and Discussion 184 9.5 Conclusion 186 10 Multiclass Classification of Oral Diseases Using Deep Learning Models 189Mohammed Zubair Hussain, Shrey Gupta, Bhagyashree Hambarde, Priya Parkhi and Zafar Karimov 10.1 Introduction 190 10.2 Literature Review 191 10.3 Methodology 193 10.4 Results 202 10.5 Conclusion 205 11 Smart Wearable Devices for Remote Patient Monitoring in Healthcare 209Ravi Mishra, Swati Chaitandas Hadke, Devanand Bhonsle, Priti Nilesh Bhagat, Anupama Mahabansi and Sheetal Mungale 11.1 Introduction 210 11.2 Wearable Devices for Remote Monitoring 213 11.3 Communication Technologies for Remote Healthcare Monitoring 218 11.4 Proposed Methodology 219 11.5 Conclusion 221 12 Efficient IoT Solutions for Remote Health Monitoring 225Vijayakumar S., N. Sheik Hameed, Kanchan S. Tiwari, A. Allwyn Sundarraj, N. Gopinath and Lyndsay R. Buckingham 12.1 Introduction 226 12.2 Related Works 228 12.3 Methodology 231 12.4 Discussion 246 12.5 Conclusion 251 13 Smart Medication Dispensing: IoT Innovations in Drug Development 255Sapna Singh Kshatri, Mukesh Kumar Chandrakar, Devanand Bhonsle, Manjushree Nayak, Prashant Tamrakar and Pramisha Sharma 13.1 Introduction 256 13.2 Problem Identification 258 13.3 Proposed Method 259 13.4 Applications 266 13.5 Use of ATMEGA328P Using Arduino 268 13.6 Software Used 272 13.7 Result and Discussion 274 13.8 Conclusion 275 14 Telemedicine and Virtual Health: Pioneering Innovation and Future Frontiers in Personalized Patient Care 279R. Rahul, R. Raghul Jayaprakash, M. Shibhi Varmaah and S. Velmurugan 14.1 Introduction to Telemedicine and Virtual Health 280 14.2 Challenges in Telemedicine 283 14.3 Artificial Intelligence in Telemedicine 289 14.4 Neurofeedback and Brain-Computer Interfaces (BCIs) in Telemedicine 292 14.5 Blockchain Technology in Virtual Healthcare 297 14.6 Telemedicine for Personalized Patient Care 301 14.7 Future Directions of Telemedicine in Healthcare 307 15 Blockchain Algorithm: Revolutionizing Healthcare Systems 313Ritika Awasthi and Arvind Tiwari 15.1 Introduction 314 15.2 How Blockchain can Relate to Healthcare 315 15.3 Literature Review 317 15.4 Features of Blockchain 320 15.5 Blockchain Algorithms 323 15.6 Network Model in Blockchain Algorithm 329 15.7 Data Collection and Storage 335 15.8 Diversity in Blockchain Technology 337 15.9 Limitations of Blockchain 339 15.10 Conclusion 341 15.11 Future Work 342 16 Enhancing Cyber-Physical System Security in Healthcare Through Ensemble Learning, Blockchain and Multi-Attribute Feature Selection 349Jagdish Pimple and Avinash Sharma 16.1 Introduction 350 16.2 Literature Survey 355 16.3 Identification of the Problem 362 16.4 Objectives 363 16.5 Proposed Methodology 364 16.6 Result and Discussion 367 16.7 Conclusion and Future Work 371 17 Digitizing Wellness: A Deep Dive Into EHR/EMR Systems 375Parul Dubey, Anansingh Thinakaran and Rajendra Motiramji Rewatkar 17.1 Introduction 376 17.2 Literature Review 376 17.3 AWS and Healthcare Solutions 378 17.4 AWS Services for Healthcare 379 17.5 Building EHR/EMR Solutions on AWS 381 17.6 Innovating with AI and Analytics 383 17.7 Case Studies 388 17.8 Proposed Architecture Overview 390 17.9 Conclusion 392 18 Harmony in Healthcare: Implementing an AI-Powered Biometric System 397S. Sharmila, M. Nirmala, Somasundaram Devaraj and M. Menagadevi 18.1 Introduction to Biometric System 398 18.2 Types of Biometric Systems 398 18.3 Biometrics in Healthcare Application 404 18.4 Biometric System for Monitoring and Disease Diagnosis 409 18.5 Future Direction of Biometrics in Personalized Care 415 19 Investigating the Revolution of Healthcare Application with Intense Comparisons and Case Study 421Amudhavalli P., S. Urmela, Vishnupriya G., N. Gopinath, R. Anandh and Lyndsay R. Buckingham 19.1 Introduction 422 19.2 Digital Twin 424 19.3 Case Study--Healthcare Applications 434 19.4 Future Research Ideas 440 19.5 Conclusion 441 References 442 Index 447

The book explores the fundamental principles and transformative advancements in cutting-edge algorithmic technologies, detailing their application and impact on revolutionizing healthcare. This book provides an in-depth account of how technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are reshaping healthcare, transitioning from traditional diagnostic and treatment approaches to data-driven solutions that improve predictive accuracy and patient outcomes. The text also addresses the challenges and considerations associated with adopting these technologies, including ethical implications, data security concerns, and the need for human-centered approaches in algorithmic medicine. After introducing digital twin technology and its potential to enhance healthcare delivery, the book examines the broader effects of digital technology on the healthcare system. Subsequent chapters explore topics such as innovations in medical imaging, predictive analytics for improved patient outcomes, and deep learning algorithms for brain tumor detection. Other topics include generative adversarial networks (GANs), convolutional neural networks (CNNs), smart wearables for remote patient monitoring, effective IoT solutions, telemedicine advancements, and blockchain security for healthcare systems. The integration of biometric systems driven by AI, securing cyber-physical systems in healthcare, and digitizing wellness through electronic health records (EHRs) and electronic medical records (EMRs) are also discussed. The book concludes with an extensive case study comparing the impacts of various healthcare applications, offering insights and encouraging further research and innovation in this dynamic field. Audience This book is suitable for academicians and professionals in health informatics, bioinformatics, biomedical science and engineering, artificial intelligence, as well as clinicians, IT specialists, and policymakers in healthcare.