Smart Healthcare and Machine Learning (Advanced Technologies and Societal Change)

About This Book
Contents
1 Big Data Analytics for Big Medical Data—Tools Applications and Challenges
	Introduction
	Health Data Sources
	Big Data Analytics in Health Care
	Tools for Big Data Analytics
	Big Data Analytics Applications in Healthcare Domain
	Big Data Analytics Challenges in Health Care
	Conclusions
	References
2 AB-BiL: A Deep Learning Model to Analyze Depression Detection in Imbalanced Data
	Introduction
	Related Work
	Proposed Model
		AdaBoost
		Bi-LSTM Model
	Experimental Results
		Dataset Description
	Conclusion
	References
3 Synchronization Analysis of Complex-Valued Artificial Neural Networks with Distributed Delays in Medical Image Processing
	Introduction
	Problem Formulation and Preliminaries
		Notations
		Complex Algebra
		Problem Formulation
		Preliminaries
	Global Exponential Synchronization Analysis
	Numerical Example
	Conclusions
	References
4 Deep Q-Learning-Based Neural Network for Secure Data Transmission in Internet of Things (IoT) Healthcare Application
	Introduction
		AI Approaches for IoT in Healthcare
		Deep Q-Learning
	Literature Review
	System Design
		Data Transmission and Scheduling Using Deep Q-Learning
		Framework for Security Systems
	Result and Discussion
		Performance Evaluation Matrix
		Accuracy
		Sensitivity
		Specificity
		Time of Encryption
		Time of Decryption
	Conclusion
	References
5 Integrating Artificial Intelligence for Enhanced Tuberculosis Diagnosis and Management: A Comprehensive Analysis
	Introduction and Background
	Tuberculosis
	Tuberculosis Disease Detection
	Machine Learning Models
		Diagnosis
	Role of Machine Learning in TB Diagnosis
	Role of Deep Learning in TB Diagnosis
	Role of ANN in TB Diagnosis
	Conclusion
	References
6 An Effective Cost-Sensitive Learning Approach for Detection of COVID-19 with Lung Diseases
	Introduction
	Related Work
	Result and Discussion
	Conclusion
	References
7 IoT in Healthcare: Applications, Benefits, Challenges, and Real-Time Use Cases
	Introduction
	Previous Research on the Topics
	Background
	Converging Information Technology in Healthcare
	An Innovative, Intelligent, and Smart Healthcare System
		The Components of a Smart Healthcare System Are as Follows
		Logical Architecture of IoT Healthcare
	A Review of the Proposed Model for Monitoring Goods Carrying Vehicles During COVID-19 [38]
		Automated Vehicle Monitoring System
		Locking Mechanism with Automatic Activation
	Automated Vehicle Monitoring System (AVMS): Design Possibilities
	Cutting-Edge Innovations Regarding Health 4.0
		Internet-Based Patient Monitoring
		Apps for Mobile Phones that Are Connected to Health
	Real-Time Telemedicine
		Healthcare Tech Prospects in the Future
		Healthcare 4.0
	The Healthcare 4.0 Revolution
	Future Scope
	Conclusion
	References
8 An ML Approach to Analyze Cyberthreats and Vulnerabilities in the Healthcare Ecosystem
	Introduction
		Cyberthreats and Vulnerabilities
		Cybersecurity in Healthcare
		Smart Healthcare Ecosystem
		Internet of Medical Things (IoMT)
	Literature Review
		Security of Blockchain and AI-Empowered Smart Healthcare
		Security and Privacy Issues in Modern Healthcare Systems: Attacks and Defenses
		Cybersecurity for Industry 4.0 in the Current Literature
		Industry 4.0 Applications for Medical/Healthcare
		War, Health and Ecosystem: Generative Metaphors in Cybersecurity Governance
		Digital Forensics for Medical Internet of Things
		Artificial Intelligence-Based Internet of Medical Things (AI-IoMT) in Smart Cities
		Cybersecurity in Smart Hospitals
	System Design
		Healthcare Ecosystem
		Logistic Regression (LR)
	Result and Discussion
		Performance Evaluation Matrix
	Conclusion
	References
9 Reliable and Efficient Healthcare System Using Artificial Intelligence
	Introduction
	Programs of Medical Informatics
		Dealing with Scientific Fields of Information
		Performing Routine Tasks
		Cure Design
		Digital Session
		Drug Advent
	Real-Time Applications of the Domains of AI
		Expert Systems
		Herbal Language Processing
		Neural Networks
		Robotics
		Fuzzy Good Judgment Structures
	Outlook of AI
	Drawbacks of Artificial Intelligence in Healthcare
	Conclusion
	Reference
10 Advancing Precision Medicine: An Exploration of Hybrid Deep Learning Approaches for Automated Human Brain Tissue Segmentation and Tumour Localization in MRI Imaging
	Introduction
	Related Works
	Literature Survey
	Result Analysis
	Conclusion
	References
11 O-RAN in Private Network for Digital Health Applications Using Twofish Encryption in the Internet of Things
	Introduction
		Twofish Encryption
		Healthcare System
		Artificial Intelligence—AI
		Machine Learning
		Supervised Learning
		Unsupervised Learning
		Deep Learning
	Literature Survey
		Study Population
		Digital Health
		Big Data Analytics
	System Design
		IoT Architecture
		Smart Sensing
		Wearable Sensors
		Twofish Encryption
	Result and Discussion
		Encryption
		Decryption Process
	Conclusion
	References
12 Mobile Nets: Prediction of Black Fungus Disease Through Image Classification
	Introduction
	Related Work
	Methodology
	Conclusion
	References
13 A Secured IoT Healthcare Architecture-Based Access Control System Using Deep Learning
	Introduction
		Health Monitoring
		Deep Learning in Healthcare
		IoT with Big Data
		Healthcare Access Control System
		IoT Applications in the Healthcare Sector
		Obstacles in the Healthcare Industry with Secure IoT
		Platforms of IoT-Based Healthcare
	Literature Review
	System Design
		Artificial Neural Network (ANN)
		Mathematical Model for ANN
	Result and Discussion
		Performance Evaluation Matrix
	Conclusion
	References
14 IoT Paradigm for Healthcare System to Secure the Patients Real-Time Data
	Introduction
		Literature Review
	Methodology
	Discussion and Findings
	Proposed Approach for Medical IoT Sensors
	Conclusions
	References
15 Application of the Internet of Things in the Healthcare Field
	Introduction
	Methodology
	Application Design
		Hardware Architecture of the Designed App
		Software Architecture of the Designed App
	Results
	Conclusion
	References
16 A Predictive Diagnostic Model for Diabetes Using Machine Learning Technique
	Introduction
	Related Work
	Methodology
		Description of the Dataset
		The Machine Learning Algorithm Used
		Model Construction
	Performance Evaluation Metrics
	Result
	Conclusion
	References
17 A Novel Development of Medical Technology and AI for Intelligent Healthcare
	Introduction
		Real-Time Usage of Intelligent Healthcare
		AI in Healthcare
		Technical Innovations
	Literature Review
	System Design
		AI for Intelligent Healthcare
		Ant Colony Optimisation (ACO)
		Convolutional Neural Network (CNN)
	Result and Discussion
		Performance Evaluation Matrix
	Conclusion
	References
18 A Blockchain-Based Hybrid SVMLR Approach for IoT-Healthcare
	Introduction
		Blockchain-Based Applications in Healthcare
		Blockchain-Based Healthcare Management Applications
	Literature Review
	System Design
		Support Vector Machine (SVM)
		Logistic Regression (LR)
	Result and Discussion
		Performance Evaluation Matrix
	Conclusion
	References
19 Non-Shannon Perspective on the IFS’s Anomalous Viable One-To-One Communication Signal Detection Pattern with Discrete Weighted Distribution
	Introduction
		Intuitionistic Fuzzy Sets
	Our Claims
	References
20 Digital Imaging and Communication in Medicine (DICOM): Biomedical and Health Informatics: Imaging and Interoperability Using HL7 and DICOM
	Introduction
	PACS and RIS
		Components of PACS
	DICOM
		Contributions of DICOM in Improving Workflow Efficiency
		DICOM File Parts
		DICOM Information Management
		Security and Ethical Considerations for DICOM Images
	HL7: Health Level Seven
		HL7 Contributions
		HL7 Messaging Standards
		Interoperability Using HL7 Messaging Standards
		Integration Support Using HL7 Messaging Standards
		HL7 Versions and Their Applications
	FHIR: The Rising Star of Interoperability
		HL7 FIHR and Patient Care
		FIHR Resources
		HL7 FIHR Implementation
	Role of DICOM and HL7 Interconnection in Medical Imaging and Healthcare Diagnostics—A Case Study Approach
		Case Study—Radiscan
		Solution
		DICOM and HL7 Interconnection
		Radiology Workflow and Information Extraction from HL7 and DICOM
	Conclusion
	References
21 Algorithms with Physics Inspiration Used in Biomedical Imaging for a Better Future
	Introduction
	Conclusion
	References