Artificial Intelligence for Smart Healthcare

Preface
Part I: Fundamentals and Applications of AI and Enabling Technologies in Various Sectors
Chapter ``A Secured Data Sharing Protocol for Minimization of Risk in Cloud Computing and Big Data in AI Application´´
Chapter ``Predictive Modelling for Healthcare Decision-Making Using IoT with Machine Learning Models´´
Chapter ``Artificial Intelligence for Smart in Match Winning Prediction in Twenty20 Cricket League Using Machine Learning Mode...
Chapter ``Comparative Analysis of Handwritten Digit Recognition Investigation Using Deep Learning Model´´
Chapter ``An Investigation of Machine Learning-Based IDS for Green Smart Transportation in MANET´´
Chapter ``A Critical Cloud Security Risks Detection Using Artificial Neural Networks at Banking Sector´´
Chapter ``A Solution to Pose Change Challenge: Real-Time, Robust, and Adaptive Human Tracking Systems Using SURF´´
Chapter ``Analysis on Identification and Detection of Forgery in Handwritten Signature Using CNN´´
Chapter ``Experimental Analysis of Internet of Technology-Enabled Smart Irrigation System´´
Chapter ``Analysis on Exposition of Speech Type Video Using SSD and CNN Techniques for Face Detection´´
Part II: AI-Enabled Innovations in the Health Sector
Chapter ``Depressive Disorder Prediction Using Machine Learning-Based Electroencephalographic Signal´´
Chapter ``Generation of Masks Using nnU-Net Framework for Brain Tumor Classification´´
Chapter ``A Brain Seizure Diagnosing Remotely Based on EEG Signal Compression and Encryption: A Step for Telehealth´´
Chapter ``A Deep Convolal Neural Network-Based Heart Diagnosis for Smart Healthcare Applications´´
Chapter ``A Dynamic Perceptual Detectors Module-Related Telemonitoring for the Intertubes of Health Services´´
Chapter ``ConvNet-Based Deep Brain Stimulation for Attack Patterns´´
Chapter ``Web-Based Augmented Reality of Smart Healthcare Education for Machine Learning-Based Object Detection in the Night S...
Chapter ``The Role of Augmented Reality and Virtual Reality in Smart Health Education: State of the Art and Perspectives´´
Chapter ``Estimation of Thyroid by Means of Machine Learning and Feature Selection Methods´´
Chapter ``A Multiuser-Based Data Replication and Partitioning Strategy for Medical Applications´´
Chapter ``A Deep Study on Thermography Methods and Applications in Assessment of Various Disorders´´
Chapter ``A Smart Healthcare Cognitive Radio System for Future Wireless Commutation Applications with Test Methodology´´
Chapter ``Indication of COVID-19 and Inference Employing RFO Classifier´´
Chapter ``Magnetic Resonance Images for Spinal Cord Location Detection Using Deep Learning Model´´
Chapter ``COVID-19 Recognition in X-Ray and CTA Images Using Collaborative Learning´´
Chapter ``Artificial Intelligence for Enhancement of Brain Image Using Semantic Segmentation CNN with IoT Classification Techn...
Part III: Security and Privacy Concerns
Chapter ``A Novel Framework for Privacy Enabled Healthcare Recommender Systems´´
Chapter ``An Evaluation of RSA and a Modified SHA-3 for a New Design of Blockchain Technology´´
Chapter ``Quality of Smart Health Service for Enhancing the Performance of Machine Learning-Based Secured Routing on MANET´´
Chapter ``Spoof Attacks Detection Based on Authentication of Multimodal Biometrics Face-ECG Signals´´
Contents
Part I: Fundamentals and Applications of AI and Enabling Technologies in Various Sectors
A Secured Data Sharing Protocol for Minimisation of Risk in Cloud Computing and Big Data in AI Application
1 Introduction
1.1 Cloud Storage for Big Data
1.2 Techniques
1.3 Extraction
2 Existing Methods
3 Proposed System
3.1 Module Implementation
3.1.1 Cloud Provider
3.1.2 Data Owner
3.1.3 The Assembly Members
4 Results and Analysis
5 Conclusion
References
Predictive Modelling for Healthcare Decision-Making Using IoT with Machine Learning Models
1 Introduction
2 Related Works
3 Machine Learning Models and Classification in Healthcare Applications
3.1 Supervised Machine Learning
3.2 Unsupervised Learning
3.3 Semi-supervised Learning
3.4 Reinforcement Learning
4 Healthcare Applications of ML in Diagnosis
5 Secure and Privacy-Preserving Use of Healthcare Measures on IoT and ML
5.1 Sources of Vulnerabilities in ML
5.2 Vulnerabilities Due to Data Annotation
5.3 Vulnerabilities in Model Training
6 Results and Discussion
6.1 Healthcare Diagnoses Outcome
6.2 Feature Predictions
7 Conclusions and Future Work
References
Artificial Intelligence for Smart in Match Winning Prediction in Twenty20 Cricket League Using Machine Learning Model
1 Introduction
2 Related Works
3 Proposed Methodology
3.1 Machine Learning Classification
3.2 Supervised Learning (SL)
3.3 Unsupervised Learning (UL)
3.4 Reinforcement Learning (RL)
4 Result and Discussions
4.1 Linear Regression (LR)
4.2 Step-by-Step Process of Machine Learning Classifications
5 Conclusion
References
Comparative Analysis of Handwritten Digit Recognition Investigation Using Deep Learning Model
1 Introduction
1.1 Abbreviations and Acronyms
1.1.1 Units
2 Related Works
3 Proposed CNN Image Classification
3.1 PReLU
3.2 Shrinking
3.3 Non-linear Mapping
3.4 Expanding
3.5 Deconvolution
4 Mathematical Model
4.1 Subsampling Layer
5 Result and Discussion
6 Conclusion
References
An Investigation of Machine Learning-Based IDS for Green Smart Transportation in MANET
1 Introduction
2 Related Works
3 Proposed ML-Based Green Smart Transportation IDS
3.1 Pre-processing and Data Augmentation
3.2 Parameters Optimization
3.3 Ensemble Learning
3.4 Algorithm 1 for ML Classification for Malicious Node Detection
3.5 Algorithm 2 for Optimal Solution for Acceptable Error Rate
3.6 Algorithm 3 for Packet Anomaly Prediction
4 Mathematical Model of ML Process
5 Result and Discussion
5.1 Simulations
5.1.1 Findings of KDD
6 Performance Analysis
7 Conclusion
References
A Critical Cloud Security Risks Detection Using Artificial Neural Networks at Banking Sector
1 Introduction
2 Artificial Neural Networks
3 Literature Survey
3.1 Cloud Computing Modeling Concepts for Banking Organizations
3.2 Cloud Security Issues
4 Methodology (Materials and Methods)
4.1 Neural Network
5 Outcomes and Discussion
6 Conclusion
References
A Solution to Pose Change Challenge: Real-Time, Robust, and Adaptive Human Tracking Systems Using SURF
1 Vision-Based Tracking
1.1 Difficulties in Visual Tracking
1.2 Required Features of Visual Tracking
1.3 Feature Descriptors for Visual Tracking
1.4 Online Learning Algorithms
1.5 Applications
2 Object Detection and Tracking
2.1 Object Representation
2.2 Object Detection
2.3 Object Tracking
2.4 Prediction Methods
3 Literature Review
4 Motivation
5 Terminology
5.1 Categorization
6 Evaluation Metrics
7 SURF-Based Algorithm to Deal with Pose Change Challenge
8 Problem Statement
9 Tracking Algorithm
10 Results
11 Conclusion
References
Analysis on Identification and Detection of Forgery in Handwritten Signature Using CNN
1 Introduction
2 Literature Review
3 Methodology
3.1 Convolution Neural Network (CNN)
3.1.1 Convolution Filtering
3.1.2 Implementation
3.1.3 Flow Diagram
3.1.4 Data Acquisition
3.1.5 Preprocessing
3.1.6 Gray to Binary
3.1.7 Noise Removal and Resizing
3.1.8 Adding CNN Layers
3.1.9 Pooling Layer
3.1.10 Flatten
3.1.11 Dense- Softmax
3.1.12 Feature Extraction
4 Results
5 Discussions
6 Conclusion
6.1 Future Scope
References
Experimental Analysis of Internet of Technology-Enabled Smart Irrigation System
1 Introduction
2 Related Study
3 Methodologies
3.1 pH Sensor
3.2 Soil Moisture Sensor
3.3 Rain Sensor
3.4 Temperature and Humidity Sensor
3.5 Cloud-Enabled Smart Agri-Handling Strategy (CSAHS)
3.6 Cloud Optimization Strategy
4 Discussion
5 Conclusion and Future Scope
References
Analysis on Exposition of Speech Type Video Using SSD and CNN Techniques for Face Detection
1 Introduction
2 Related Work
3 Approach
3.1 Single Shot Multi-box Detector (SSD)
3.2 Convolution Neural Network (CNN)
3.3 Frame Selection
3.4 VSUMM
3.5 Video Exposition
4 Results and Discussion
5 Conclusion
References
Part II: AI-Enabled Innovations in the Health Sector
Depressive Disorder Prediction Using Machine Learning-Based Electroencephalographic Signal
1 Introduction
2 Related Works
3 Scope of the Work
3.1 The Research Objective
4 Proposed Block Diagram
4.1 Overall Working Principle of EEG Signal
4.2 Procedure for PSD Calculation
4.3 Algorithm for Feature Extraction by ML Method
5 Results and Discussion
6 Conclusion and Future Work
References
Generation of Masks Using nnU-Net Framework for Brain Tumour Classification
1 Introduction
1.1 Imaging Modalities
1.2 General Analysis Objectives
2 Literature Review
3 Proposed Methodology
3.1 Materials and Methods
3.2 Experimental Setup
3.3 Model Training and Making Masks
4 Conclusion
References
A Brain Seizure Diagnosing Remotely Based on EEG Signal Compression and Encryption: A Step for Telehealth
1 Introduction
2 Related Literature Works
3 Methodology
4 Research Parameters
4.1 Exchange of Diffie-Hellman Key
4.2 Signal Block Creation
4.3 Adaptive Huffman Encoding (AdHuEn)
5 Hybrid Cryptography for EEG Signal
6 Findings and Discussion
6.1 Compression Performance
6.2 Analysing the Security of EEG Signals
7 Conclusion
References
A Deep Convolutional Neural Network-Based Heart Diagnosis for Smart Healthcare Applications
1 Introduction
2 Literature Survey
3 Methodology
4 Results and Discussion
5 Conclusion
References
A Dynamic Perceptual Detector Module-Related Telemonitoring for the Intertubes of Health Services
1 Introduction
2 Related Work
3 Data Transmission Layout Adaptation
4 Node Structure for IoMT
4.1 Platform Surface of Hardware
4.2 OS/Layer of the Load Balancer
4.2.1 FreeRTOS
4.2.2 Cortex Microcontroller
5 Approach Model
6 Assistance for Flexibility: The ADAptive Environment Scheduler
7 Use-Case Evaluation
7.1 Information Collected Is the First Intraoperative Phase
7.2 Saturation Identification Is the Client Operating Mode
7.3 Analysis of CNN o.m. in the Mode of Operation 3
8 Peak Detection
9 Activation for Neural Networks
9.1 Quantization
9.2 Investigation of Archetypes
9.3 Amplification
10 Research Outcomes
10.1 Assessment of Energy Utilization
10.2 Indicators of Electricity Consumption
10.2.1 Instance: 50 bpm
10.2.2 Instance: 100 bpm
10.2.3 Instance: 200 bpm
10.3 Estimation of Energy Usage Related to Power Model and Operation Mode
11 Conclusion
References
ConvNet-Based Deep Brain Stimulation for Attack Patterns
1 Introduction
1.1 Planning and Positioning of DBS
1.1.1 The Objective of Machine Learning (ML) Model
2 Literature Survey
2.1 Findings of Machine Learning in DBS
3 Proposed Work
3.1 Objectives of Machine Learning
3.2 Input Signal Collection
3.3 Class Separation
3.4 Rest Tremor Velocity
3.5 Parameter Setting
3.6 Convolutional Neural Network
3.7 Performance Measures for Precision, Error Rate, and Fully Connected Layers
4 Experimental Results
4.1 Software Environment
5 Conclusion
5.1 Future Work
References
Web-Based Augmented Reality of Smart Healthcare Education for Machine Learning-Based Object Detection in the Night Sky
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Sky Map
3.2 Space Catalogue
3.3 Experimental Setup
3.4 Validation
3.5 ML and OpenCV to Detect Objects
4 Dataset
4.1 Data Preparation
4.2 Metrics
5 Conclusion
References
The Role of Augmented Reality and Virtual Reality in Smart Health Education: State of the Art and Perspectives
1 Introduction
2 Augmented Reality (AR) in Education
3 Virtual Reality (VR) in Education
4 Recent Advancements of AR/VR in Education
5 Challenges of Adopting AR/VR in Education
6 Future Scope of AR/VR in Education
7 Conclusion
References
Estimation of Thyroid by Means of Machine Learning and Feature Selection Methods
1 Introduction
1.1 A General Overview of Thyroid Disease
1.1.1 The Role of the Thyroid in the Body´s Health
1.1.2 Hyperthyroidism
1.1.3 Thyroid Hormones
2 Literature Survey
2.1 Problem Declaration
2.1.1 Existing System
Limitations of Current Material
2.1.2 Proposed System
2.2 System Overview
2.3 Machine Learning Implementation
2.3.1 SVM Algorithm (Support Vector Machine)
2.3.2 KNN Algorithm (K-Nearest Neighbor)
2.3.3 NB (Naiïve Bayes)
2.3.4 The Dataset Description
2.4 Modules
2.4.1 Admin
2.4.2 User
3 Result and Analysis
4 Conclusion
References
A Multiuser-Based Data Replication and Partitioning Strategy for Medical Applications
1 Introduction
2 Related Works
2.1 Partitioning Strategies
2.2 Proposed Model
3 Conclusion
References
A Deep Study on Thermography Methods and Applications in Assessment of Various Disorders
1 Introduction
2 Materials and Methods
3 Literature Survey
3.1 Proposed System
4 Result Analysis
5 Conclusion
References
A Smart Healthcare Cognitive Radio System for Future Wireless Commutation Applications with Test Methodology
1 Introduction
1.1 MICR
2 Related Work
2.1 Cognitive Radio Definitions and Architectures
2.2 Numerical Analysis
2.3 Cognitive Radio Test Methodologies
3 Proposed Test Methodology
3.1 Overview
3.2 Benchmarks
3.3 Test Outline
4 Methodology
4.1 Approach
4.2 Evaluation Technique
4.3 Performance Metrics
4.4 Workload
4.5 System Under Test
4.6 Experimental Design
5 Results and Analysis
5.1 Effect of SU CE on SU Throughput and BER
5.2 Throughput vs BER in MICR
5.3 Scoring
6 Conclusion
References
Indication of COVID-19 and Inference Employing RFO Classifier
1 Introduction
1.1 COVID-19 and Its Effecting Elements
1.2 Immunity Issues
1.3 Vaccine and Its Working
2 Symptoms and Samples
2.1 Prevention
2.2 Diagnosis Process
2.3 RFO Methodology
3 Results and Discussion
4 Conclusion
References
Magnetic Resonance Images for Spinal Cord Location Detection Using a Deep-Learning Model
1 Introduction
2 Literature Review
3 Related Works
4 Proposed Work
4.1 Spinal Cord Centerline Recognition
4.2 Spinal Cord and Mean Segmentation
4.3 Implementation
4.4 Evaluation
4.5 Spinal Cord Centerline Recognition
4.6 Spinal Cord Segmentation
4.7 Mean Segmentation of Lesions
4.8 Inter-Rater Variability of the Mean Lesion Segmentation
5 Results
6 Conclusion
References
COVID-19 Recognition in X-RAY and CTA Images Using Collaborative Learning
1 Introduction
2 Limitations of Earlier Models
3 Methodology
3.1 System Architecture
3.2 Dataset Details
3.3 Network Training Configuration
3.4 CNN Founded Feature Separator and Classification
3.5 Segmentation of the COVID-19-Affected Region
4 Results
5 Conclusion
References
Artificial Intelligence for Enhancement of Brain Image Using Semantic Segmentation CNN with IoT Classification Techniques
1 Introduction
2 Literature Survey
3 Proposed System
3.1 Semantic Segmentation
4 Result and Discussion
5 Conclusion
References
Part III: Security and Privacy Concerns
A Novel Framework for Privacy Enabled Healthcare Recommender Systems
1 Introduction
2 Materials and Methods
2.1 Background
2.1.1 Users Health Data Concerns
2.1.2 Data Breaches: US Data (2010-2020)
2.2 Privacy Aspects in Healthcare System
2.3 Existing Privacy Enabled Healthcare Recommender System
3 Results
3.1 Proposed Healthcare Recommender System
3.1.1 Steps of Recommendation Generation Through Our Framework
4 Discussion
5 Conclusion
References
An Evaluation of RSA and a Modified SHA-3 for a New Design of Blockchain Technology
1 Introduction
2 Related Work
3 SHA-3 and RSA Algorithm
3.1 SHA-3
3.2 RSA Algorithm
4 Proposed System
4.1 First Part: The Client
4.2 Second Part: The Server
4.3 Improve Modification RSA Algorithm (IM_RSA)
4.4 Lightweight Hash Function
5 Result and Discussion
6 NIST Statistical Suite Tests
7 Conclusion
References
Quality of Smart Health Service for Enhancing the Performance of Machine Learning-Based Secured Routing on MANET
1 Introduction
2 Related Works
2.1 Cross Layered QoS Routing
2.2 Assessing the Rate of Packet Losses
3 Assessing Connection Delays
4 Purpose of Routing Parameters
5 QoS Forwarding
6 Performance Analysis
6.1 Results and Discussion
6.2 Average Delays
6.3 Network Throughput
7 Rate of Packet Delivery
8 Congestion Overheads
9 Conclusion
References
Spoof Attacks Detection Based on Authentication of Multimodal Biometrics Face-ECG Signals
1 Introduction
2 Review of Related Literature
3 Biometric System Attacks Patterns
3.1 Direct Attack Pattern
3.2 Indirect Attack Pattern
4 Current Techniques and Its Restrictions
5 The Proposed Techniques and Its Benefits
5.1 Face Based Biometric Authentication
5.2 Facial Recognition Data Collection (FRDC)
5.3 ECG Signals-Based Biometric Authentication
5.4 ECG Signal Acquisition
6 Resist Attacks Techniques (RAT)
6.1 Vitality Detecting Method (VDM)
6.2 Cryptosystems Biometric
6.3 Avoid the Artefacts
6.4 Artefacts Cancelation
6.5 Channel Selection
7 Feature Extracting
8 Frequency Domain Approaches
9 Data Reduction
10 Classification
11 Face and ECG Fusion
11.1 Proposed MMB Authentication Using Face and ECG
12 Results and Outcomes
13 Conclusion
References
Index