Intelligent Interactive Multimedia Systems for e-Healthcare Applications

This book includes high-quality research on various aspects of intelligent interactive multimedia technologies in healthcare services. The topics covered in the book focus on state-of-the-art approaches, methodologies, and systems in the design, development, deployment, and innovative use of multimedia systems, tools, and technologies in healthcare. The volume provides insights into smart healthcare service demands. It presents all information about multimedia uses in e-healthcare applications. The book also includes case studies and self-assessment problems for readers and future researchers. This book proves to be a valuable resource to know how AI can be an alternative tool for automated and intelligent analytics for e-healthcare applications. Preface Contents About the Editors Introduction About Intelligent Systems and Multimedia Systems for Healthcare Comparison, Analysis and Analogy of Biological and Computer Viruses 1 Introduction 2 Background 2.1 Biological Virus 2.2 Computer Virus 3 Biological Viruses 3.1 Origin 3.2 Architecture 3.3 Mutation 3.4 Propagation 3.5 Functioning and Impact 3.6 Effect and Infect with Its Detection and Emergence 3.7 Prevention 3.8 Infection Encountered 3.9 Coronavirus (COVID-19) 4 Computer Virus 4.1 Origin 4.2 Architecture 4.3 Functioning and Propagation 4.4 Infects and Its Detection 4.5 Infections Encountered 4.6 Code Red 4.7 MBR—Rewriting Malware (COVID-19 Virus) 4.8 Ransomware 5 Analysis Between Biological Virus and Computer Virus 6 Conclusion References Role of AI and AI-Derived Techniques in Brain and Behavior Computing 1 Introduction 1.1 EEG Artifacts 1.2 Brain–Computer Interface (BCI) 1.3 Challenges in the Field of BCI Implementation 1.4 EEG Databases 2 Machine Learning 2.1 Supervised Learning 2.2 Unsupervised Learning 2.3 Reinforcement Learning 3 Available Tools for ML and BCI 4 Classification Algorithms in Machine Learning 4.1 Performance Parameters 4.2 Existing Machine Learning-Based BCI Classification Methods 5 Clustering Algorithms in BCI 5.1 Performance Parameters in Clustering Algorithms 5.2 The Existing Clustering Method in BCI 6 Deep Learning 6.1 Popular DL Models in Machine Learning 6.2 Long Short-Term Memory 7 Conclusion References Applications of Intelligent System in Healthcare Innovative Services Using Cloud Computing in Smart Health Care 1 Introduction 2 Cloud Computing 2.1 Features of Cloud Computing 2.2 Cloud Service Models 2.3 Cloud Deployment Model 3 Present Status of Healthcare Industries 4 Cloud Computing in Medical Services 5 Benefits of Cloud Computing in Healthcare Industry 6 Cloud Computing Services to Medical Services Industry 7 Importance of Cloud Adoption in Health Care 8 COVID-19 Impact on Cloud Computing in Healthcare Industry 9 Deal with the Cloud Environment 10 Conclusion References Toward Healthcare Data Availability and Security Using Fog-to-Cloud Networks 1 Introduction 2 Background 2.1 IoHT Systems 2.2 Benefits of IoHT 2.3 Cloud Network 2.4 The Cloud Challenges 2.5 DDoS in IoHT 3 Literature Review 4 Fog Computing Paradigm 4.1 The Cloud and Fog Computing Differences 4.2 Fog Computing Benefits in IoHT 5 Leveraging IoHT Cloud Services with Fog Network 6 Proposed Framework 6.1 Problem Formulation 7 Result Discussion 8 Conclusion References Gestation Risk Prediction Based on Feature Extraction and Neural Networks 1 Introduction 2 Review of Literature 3 Problem Statement 3.1 Research Gap for Gestation Related Processes 4 Proposed Knowledge-Based Graph Embedding Representation with DNN (KGER-DNN) 5 Deep Neural Network-Based 6 Risk Assessment 7 Performance Analysis 7.1 Dataset Description 8 Conclusion References Smart Healthcare System: Interface to COVID-19 Prevention Using Dual-Layer Security 1 Introduction 2 Methodology and Approach 3 Methodology 4 Result and Discussion 4.1 Face Detection Recognition System 4.2 Image Enhancement 4.3 FEP-RSA-MM Testing 4.4 Correlation-Based Matching 4.5 Combined Face Recognition, EEG, and RSA 5 Conclusion and Future Work References Pregnancy Women—Smart Care Intelligent Systems: Patient Condition Screening, Visualization and Monitoring with Multimedia Technology 1 Introduction 2 Related Work 3 Health Monitoring Based on IoT System 3.1 Heartbeat Measurement 3.2 Temperature Measurement 3.3 Fetal Movements 3.4 Hardware Setup 3.5 Experimentation and Result 4 Health Monitoring System Based on Biosignal Analysis 4.1 Biosignal 4.2 Dataset 4.3 Preprocessing 4.4 Analysis 4.5 Experimentation and Result 5 Health Monitoring Based on Smart Wearable Devices 5.1 Methodology 5.2 Smart Wristband as a Measurement Tool 5.3 Data Collection and Outcomes 5.4 Data Analysis 5.5 Experimentation and Result 6 Conclusion References Prediction of COVID-19 Outbreak with Current Substantiation Using Machine Learning Algorithms 1 Introduction 1.1 Study Area 1.2 Industrial Background 1.3 Virudhunagar District Covid-19 Cases 2 Material and Methods 2.1 Proposed System Procedure 2.2 Data Collection 2.3 Classification and Prediction Algorithm 2.4 Neural Network Steps 2.5 Performance Testing 3 Results and Discussion 3.1 Age Group 3.2 Analysis of Regions 3.3 Classification of COVID 19 3.4 Performance Metrics 3.5 Research Opportunities and Emerging Trends 4 Conclusion References Artificial Intelligence and an Edge-IoMT-Based System for Combating COVID-19 Pandemic 1 Introduction 2 Opportunities for Deploying the Artificial Intelligence and IoMT Technologies During COVID-19 Pandemic 3 Application of Edge Computing During Coronavirus Outbreak 4 Artificial Intelligence in Fighting COVID-19 Pandemic 5 Proposed Architecture for the Monitoring of COVID-19 Patient 6 The Practical Implementation Scenario of the Proposed Framework 6.1 The Following are Practical Applications of the Proposed Framework 7 Conclusion and Future Research Directions References Artificial Intelligence Based Diagnostic Model for the Detection of Malaria Parasites from Microscopic Blood Images 1 Introduction 2 Related Works 3 Proposed Methodology 3.1 Image Denoising Using k-SVD 3.2 Blood Image Segmentation 3.3 Feature Extraction 4 Feature Selection Through Random Forest 4.1 Feature Selection 5 Malaria Parasites Classification Through Machine Learning Techniques 5.1 Random Forest 6 Experimental Results and Discussions 7 Conclusions References Issues and Challenges Towards Intelligent System in Healthcare Imposing Security and Privacy in the Healthcare Industry Using Blockchain Technology 1 Basic Concepts of Blockchain 1.1 Structure of Blockchain 1.2 Module Creation in Blockchain Technology 2 Research Background of Blockchain 2.1 Developing Trend 2.2 Blockchain 1.0 and 2.0 2.3 Blockchain 3.0 2.4 Common Aspects of Blockchain 2.5 Modes of Blockchain 3 Cyber Security Threats and Incidents on Blockchain 4 Categorization of Blockchain Threats and Vulnerabilities 4.1 Client’s Vulnerabilities 4.2 Consensus Mechanism’s Vulnerability 4.3 Mining Pool Vulnerability 4.4 Network Vulnerability 4.5 Smart Contract Vulnerability 5 Blockchain-Based Security 5.1 P2P Network 5.2 P2P-Based M2M Applications and Security Issues 6 Blockchain-Based Security 6.1 Motivation 6.2 Problem Statement 6.3 Contributions 6.4 Asymmetric Encryption 6.5 Smart Contract 7 Essential Technologies of Blockchain Security, Privacy, and Trust 7.1 Encryption Technology Related to Security 7.2 Hash Function, Merkle Tree Related to Privacy 7.3 Consensus Mechanism Related to Trust 7.4 Smart Contract 8 Security and Privacy in Blockchain 9 Open Research Challenges 9.1 Future Research Directions 10 Conclusion References Industry 4.0 Challenges in e-Healthcare Applications and Emerging Technologies 1 Introduction 2 Organization of the Work 3 Literature Review 4 Self-determination Medicine for Healthcare 5 Internet of Things and Big Data: A Revolution in Biomedical Industry 5.1 Internet of Things and Big Data Technology for Personalized Medicine 5.2 Internet of Things and Big Data Technology for Next Generation Based Healthcare 5.3 Role of Artificial Intelligence in HealthCare 6 Data Mining: A New Hope in Healthcare System 6.1 Intelligent Heart Disease Prediction System 6.2 Diagnosis and Prognosis of Cancer Disease 6.3 Customer Relationship Management (CRM) Systems 6.4 Avoidance and Early Detection of Various Frauds in Healthcare Industry 7 Introduction of Cyber Physical System in Healthcare Industry 8 Opportunities and Challenges in e-Healthcare System in this Smart Era 9 Conclusion References Security, Privacy and Trust Issues in Internet of Things and Machine Learning Based e-Healthcare 1 Introduction—Internet of Things (IoT) and Machine Learning in e-Healthcare 2 Background Study 3 Internet of Medical Things (IoMT): Future of Healthcare 4 Development of Personalized Medicine Using Internet of Things and Machine Learning 5 Applications of Internet of Things in Healthcare Industry: Internet of Things for All 6 Application of Machine Learning in Healthcare Industry 7 Security and Privacy Issues of Internet of Things and Machine Learning in e-Healthcare 8 Popular Attacks on Healthcare Systems 9 Existing Methods to Address Security and Privacy Issues 10 Conclusion References Future of Intelligent System in Healthcare and Other Sectors Industry 4.0: A Revolution in Healthcare Sector via Cloud, Fog Technologies 1 Introduction 2 Health Sector-Industry Technologies 4.0 3 ICT Pillars for Healthcare 4.0 (HC4.0) 3.1 HC4.0 and Internet of Things 3.2 HC4.0 and Cloud and Fog Computing 3.3 HC4.0 and Big Data 4 Use Cases: HC4.0 Application Scenarios 4.1 Physiological and Pathological Signs Tracking 4.2 Self-management, Tracking of Wellbeing, and Prevention 4.3 Monitoring of Drug Intake and Smart Pharmaceuticals 4.4 Healthcare Customization 4.5 Health Information Systems Based on the Cloud 4.6 Telepathology, Telemedicine, and Control of Illnesses 5 Challenges 5.1 IoT 5.2 Cloud and Fog Computing 5.3 Big Data 6 Conclusion References Blockchain Technology for Securing Cyber-Infrastructure and Internet of Things Networks 1 Introduction 2 Related Work 3 Motivation 4 Necessity of Cyber-Infrastructure in Current Century 5 Tools Available for Securing Cyber-Infrastructure and Internet of Things-Based Infrastructure 6 Issues, Problems and Challenges in Using Blockchain Technology During Securing Respective Infrastructure 7 Opportunities for Blockchain, Cyber and Computer Security Community 8 Summary References AI Approach Based on Deep Learning for Classification of White Blood Cells as a for e-Healthcare Solution 1 Introduction 2 Cognitive Computing Concept 3 Neural Networks Concepts 3.1 Convolutional Neural Network 4 Metaheuristic Algorithm Proposal 5 Results and Discussion 6 Future Research Directions 7 Conclusions References Extreme Learning-Based Intellectual Lung Cancer Classification Using Artificial Intelligence 1 Introduction 2 Literature Works 3 The ELM Methodology 3.1 Preprocessing of Data 3.2 Lung Cancer Segmentation Using Marker Controlled Watershed Algorithm 3.3 Feature Extraction 3.4 Optimized Feature Selection Using PSO 3.5 Feature Classification Using ELM 4 The Outcomes and Discussions 5 Conclusion References Cancer Patient Healthcare Analysis by Genomic Prediction 1 Introduction 2 Related Work 3 About Genomic Analysis of Cancer 4 Methodology 4.1 Hybrid Discriminant Analysis (HDA) 4.2 PCA 4.3 LDA 5 Implementation Results 6 Conclusion 7 Future Enhancement References The World with Future Technologies (Post-COVID-19): Open Issues, Challenges, and the Road Ahead 1 Introduction 2 Comparison of Scope of Machine Learning Techniques Pre-COVID and Post-COVID-19 Era 3 Motivation 4 Artificial Intelligence in Health Care and Other Sectors: Hope or Hype? 5 Emerging Techniques for Automotive (Connected and Autonomous Cars) Security 6 Security and Standardization for Smart and Critical Applications 6.1 Blockchain-Based Security in Critical Applications 6.2 Machine and Deep Learning-Based Security Techniques for Critical Applications 6.3 Application Programming Interface (API) Security for Critical Applications 6.4 Authentication and Identity Management in Smart Applications 6.5 Standardization Activities for Securing Smart and Critical Applications 7 Security Issues in Finance and Banking and Solutions in Many Other Applications Through Emerging Techniques 8 Privacy Issues in e-Healthcare, Telecommunication, and Other Applications Through Emerging Techniques 9 Open Issues and Critical Challenges with Future Technology/Toward Post-COVID-19 Era 9.1 Internet of Things and Cloud Computing in Post-COVID-19 Era: Applications and Challenges 9.2 Internet of Things Challenges and Solutions 9.3 Cloud Computing Challenges and Solutions 10 The Road Ahead with Future Technology: Future Research Directions 10.1 Advanced Analytics with Machine Learning: A Way to Forward 10.2 Future Research Directions for Machine Learning Toward Internet of Things-Based Cloud Applications 11 Conclusion References