Healthcare 4.0: Health Informatics and Precision Data Management

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Editor Biography
List of Contributors
Chapter 1: Privacy-preserving Healthcare Informatics using Federated Learning and Blockchain
1.1 Introduction
1.2 Electronic Health Record Management and Informatics
1.2.1 Information Retrieval System for Healthcare Informatics
1.2.2 Privacy and Security in E-health Records
1.2.3 Healthcare Informatics and Bigdata
1.2.4 Enabling Technologies – Fog Computing, Blockchain, Internet of Things
1.3 Federated Learning
1.3.1 Massive Non-identically Independent Distribution
1.3.2 Horizontal Federated Learning
1.3.3 Vertical Federated Learning
1.3.4 Federated Transfer Learning in Healthcare Informatics
1.3.5 Privacy Preservation in Federated Learning
1.3.6 Statistical Challenges of Federated Learning
1.4 Blockchain in Healthcare Informatics
1.4.1 Blockchain Distributed Ledger for Healthcare Informatics
1.4.2 Healthcare Framework with Blockchain
1.4.3 Key Challenges of Blockchain in Healthcare Systems
1.4.4 Future Healthcare with Security
1.5 Differential Privacy Preservation in Healthcare Data
1.5.1 Deep Learning Models for Privacy Preservation
1.5.2 Adaptive Laplace Mechanism
1.5.3 Local Differential Privacy Preservation
1.5.4 Differential Privacy in Blockchain
1.6 Improved Federated Leaning–fusion Learning
1.7 Visualizing Knowledge Structure in Healthcare Informatics
1.8 Conclusion
References
Chapter 2: Applications, Opportunities, and Current Challenges in the Healthcare Industry
2.1 Healthcare Introduction
2.2 Healthcare Data
2.3 Healthcare Research Issues
2.4 Healthcare Blockchain Systems
2.5 Healthcare Analytics
2.5.1 Types of Analytics
2.6 Healthcare Applications
2.6.1 Applications for Patients
2.6.2 Applications for Healthcare Professionals
2.6.3 Applications for Resource Management
2.7 Security and Privacy
2.8 Conclusion
References
Chapter 3: Harnessing Big Data and Artificial Intelligence for Data Acquisition, Storage, and Retrieval of Healthcare Informatics in Precision Medicine
3.1 Introduction
3.2 Biomedical Informatics and Precision Medicine: Healthcare 4.0
3.3 Data Acquisition system
3.3.1 Protocols of Data Acquisition System
3.3.1.1 Advanced Message Queuing Protocol
3.3.1.2 Java Message Service
3.3.2 Open Source Data Acquisition Frameworks
3.3.2.1 Storm
3.3.2.2 Simply Scalable Streaming System (S4)
3.3.2.3 Kafka
3.3.2.4 Flume
3.3.2.5 Hadoop
3.3.2.6 Flink
3.4 Storage of Data
3.4.1 Bigdata in Biomedical Informatics
3.4.2 Intelligent Medical Big Data System with Hadoop and Blockchain
3.4.2.1 Hadoop Architecture
3.4.2.2 Hadoop Distributed File System
3.4.2.3 Apache HBase
3.4.3 Cloud Computing in Healthcare
3.4.4 IoT Applications for Healthcare
3.4.5 Integration of Cloud and IoT
3.4.6 Enabling Security for Cloud data
3.4.6.1 Blockchain
3.4.6.2 Integration of Cloud and Blockchain
3.4.6.3 Integration of Cloud and Blockchain in Healthcare
3.4.6.4 Fog Computing in Health Sector
3.5 Information Retrieval
3.5.1 Query Expansion
3.5.2 Content-Based Medical Visual Information Retrieval
3.5.3 Fusion Technique in Biomedical Information Retrieval
3.5.4 Tag-Based Information Retrieval
3.5.5 Biomedical Word Embedding
3.6 Discussion and Future Directions
3.7 Conclusion
References
Chapter 4: Analogous Healthcare Product Identification in Online Shopping
4.1 Introduction
4.2 Content-Based Image Recovery
4.3 Text-Based Image Recovery
4.4 Retrieval by Colour
4.5 Existing Method
4.5.1 Drawback
4.6 The Proposed Method
4.7 Conclusion
References
Chapter 5: Segmentation-based Comparative Analysis for Detection of Bone Tumour Using Healthcare Data
5.1 Introduction
5.2 Literature Survey
5.2.1 Image Capture and Display
5.2.2 The Biological Significance of Bone
5.2.3 Conversion of a Picture into a Greyscale Level
5.2.4 Preparation of the Material
5.3 Main Contributions
5.3.1 Outline of the Paper
5.4 Segmentation
5.5 Classification
5.5.1 Min/Max Algorithm For Graph Cuts
5.6 Existing System
5.7 Proposed System
5.8 Result and Observations
5.9 Conclusion
References
Chapter 6: Challenges, Progress and Opportunities of Blockchain in Healthcare Data
6.1 Different Ways of Managing Healthcare Data
6.1.1 Patient Maintains Their Records
6.1.2 Hospitals Maintain Patient Records on Local Servers
6.1.3 Hospitals Maintain Patient Records on Centralized Servers
6.1.4 Hospitals Maintain Patient Records in the Cloud
6.1.5 Drawbacks in Current Technology
6.2 Introduction of Blockchain
6.2.1 Secure Hash Algorithm in Blockchain
6.3 Application of Blockchain
6.4 Need for Blockchain in Healthcare
6.4.1 Advantages of Distributed Storage in Blockchain
6.5 Managing Patient Health Data in Blockchain
6.6 Working on Blockchain in Health Data
6.7 Literature Review
6.8 Challenges of Blockchain in Health Data
6.8.1 Technical Challenges
6.8.2 Organizational Challenges
6.8.3 Government Policy Challenges
6.9 Opportunities for Blockchain in Health Data
References
Chapter 7: SepSense: A Novel Sepsis Detection System Using Machine Learning Techniques
7.1 Introduction
7.2 Related Works
7.3 Proposed System
7.3.1 Data Preprocessing
7.3.2 Classification
7.3.3 Model Selection
7.4 Implementation and Results
7.5 Conclusion
References
Chapter 8: Oral Cancer Detection at Early Stage Using Convolutional Neural Network in Healthcare Informatics
8.1 Introduction
8.2 Literature Survey
8.3 Existing System
8.4 Proposed Method
8.4.1 Image Processing System
8.4.1.1 Digitizer
8.4.1.2 Image Processor
8.4.1.3 Image Processing Fundamental
8.5 Methodology
8.5.1 Input Image and Pre-processing
8.5.2 Resizing Images and Changing the Colour Space
8.5.3 Gaussian Filtering and Gamma Correction
8.5.4 Segmentation
8.5.5 Colour Space Conversions
8.6 CNN
8.6.1 Operation
8.7 Image Feature Detector
8.8 Trainee
8.9 Results and Discussion
8.9.1 Performance Measures
8.9.2 Image Classification Result
8.9.3 Object Detection Result
8.10 Conclusion
References
Chapter 9: Lung Diseases Identification
9.1 Introduction
9.1.1 Squamous Cell Lung Cancer in the Early Stages
9.1.2 Advanced Small Cell Lung Cancer in the Extensive Stage
9.1.3 Difficulties in Determining the Nature of Lung Cancer Cells
9.2 Literature Survey
9.3 Proposed Method
9.3.1 Input Image
9.3.2 Preprocessing
9.3.3 Segmentation
9.3.4 Feature Extraction
9.3.5 Classification
9.4 Result and Output
9.5 Conclusion
References
Chapter 10: Brain–Computer Interface-based Real-Time Movement of Upper Limb Prostheses
10.1 Introduction
10.1.1 Motor Imagery Signal Decoding
10.2 Literature Survey
10.3 Methodology of the Proposed Work
10.3.1 Proposed Control Scheme
10.3.2 One Versus All Adaptive Neural Type-2 Fuzzy Inference System (OVA-ANT2FIS)
10.3.3 Position Control of Robot Arm Using Hybrid BCI for Rehabilitation Purpose
10.3.4 Jaco Robot Arm
10.3.5 Scheme 1: Random Order Positional Control
10.4 Experiments and Data Processing
10.4.1 Feature Extraction
10.4.2 Performance Analysis of the Detectors
10.4.2.1 Scheme 1
10.4.3 Performance of the Real-Time Robot Arm Controllers
10.5 Discussion
10.6 Future Research Directions
References
Chapter 11: A Robust Image-Driven CNN Algorithm to Detect Skin Disease in Healthcare Systems
11.1 Introduction
11.2 Related Work
11.3 Materials and Methods
11.3.1 Local Ternary Pattern
11.3.2 Splitting LTP into Two LBP Channels
11.3.3 Gray-Level Co-Occurrence Matrix
11.3.4 Morphological Process
11.3.4.1 Back Propagation Networks
11.3.4.2 Back Propagation Algorithm
11.3.4.3 Steps of the Algorithm
11.3.4.4 Removing Unnecessary Neurons
11.3.4.5 Contour Detection
11.3.5 Threshold Segmentation
11.4 Results and Discussions
11.5 Conclusion
References
Chapter 12: Patient Identity Ailments and Maintenance Using Blockchain and Health Informatics
12.1 Introduction: Background and Research Motivation
12.1.1 Background and Research Motivation
12.2 Hyperledger Fabric
12.3 Proposed Patient Identity Hyperledger Architecture
12.4 Proposed Architecture Implementation
12.4.1 Registering the Users
12.4.2 Adding EHR Record to the Blockchain
12.4.3 Self-Sovereign Identity for the Patients
12.4.4 Retrieving the Record
12.5 Security Analysis Using Use Case Scenarios
12.5.1 Use Case 1: Enhanced Security
12.5.2 Use Case 2: Efficient Health Records Storage
12.5.3 Use Case 3: Improved Data Privacy
12.5.4 Use Case 4: Better Data Scalability
12.6 Performance Analysis and Discussion
12.7 Conclusion
References
Chapter 13: An Innovative Outcome of Internet of Things and Artificial Intelligence in Remote Centered Healthcare Application Schemes
13.1 Introduction
13.2 Machine Learning Applications
13.3 Related Works
13.4 Background
13.5 Collection and Transmission of Information
13.6 Record Establishment to Do Disease Diagnosis
13.7 System Architecture
13.8 Cloudlet Processing
13.8.1 Cloud Computing in Healthcare
13.8.1.1 Cost Reduction
13.8.1.2 Facilitating the Interaction
13.8.1.3 Access to Performance Analysis
13.9 Proposed Methodology
13.9.1 System Modules
13.9.1.1 Healthcare Monitoring Section
13.9.1.2 Emergency Alert and Notification Section
13.9.1.3 Health Status Predictor
13.10 Implementation
13.10.1 Raspberry Pi
13.10.2 Temperature Sensor
13.10.3 Heartbeat Sensor
13.10.4 Vibration Sensor
13.10.5 BP Sensor
13.10.6 Analog-to-Digital Converter
13.10.7 Global System for Mobile Communications Module
13.10.8 Camera Specifications
13.11 ML for Health Care: The Challenges
13.11.1 The Safety Challenge
13.11.2 Personal Obstacles to Overcome
13.11.3 Ethical Issues to Consider
13.12 Conclusion
13.13 Future Work
References
Chapter 14: Electronic Health Records Storing and Sharing System Using Blockchain
14.1 Introduction
14.1.1 Blockchain
14.1.2 Types of Blockchain
14.1.3 Smart Contract
14.1.4 Ganache
14.2 Proposed System
14.3 Methodology
14.4 Results
14.5 Conclusion
References
Index