Big Data Analytics for Intelligent Healthcare Management

Cover
Big Data Analytics for
Intelligent Healthcare
Management
Copyright
Contributors
Preface
Acknowledgments
1
Bio-Inspired Algorithms for Big Data Analytics: A Survey, Taxonomy, and Open Challenges
	Introduction
		Dimensions of Data Management
	Big Data Analytical Model
	Bio-Inspired Algorithms for Big Data Analytics: A Taxonomy
		Evolutionary Algorithms
		Swarm-Based Algorithms
		Ecological Algorithms
		Discussions
	Future Research Directions and Open Challenges
		Resource Scheduling and Usability
		Data Processing and Elasticity
		Resilience and Heterogeneity in Interconnected Clouds
		Sustainability and Energy-Efficiency
		Data Security and Privacy Protection
		IoT-Based Edge Computing and Networking
	Emerging Research Areas in Bio-Inspired Algorithm-Based Big Data Analytics
		Container as a Service (CaaS)
		Serverless Computing as a Service (SCaaS)
		Blockchain as a Service (BaaS)
		Software-defined Cloud as a Service (SCaaS)
		Deep Learning as a Service (DLaaS)
		Bitcoin as a Service (BiaaS)
		Quantum Computing as a Service (QCaaS)
	Summary and Conclusions
	Acknowledgments
	References
	Further Reading
2
Big Data Analytics Challenges and Solutions
	Introduction
		Consumable Massive Facts Analytics
		Allotted Records Mining Algorithms
		Gadget Failure
		Facts Aggregation Challenges
		Statistics Preservation-Demanding Situations
		Information Integration Challenges
	Records Analysis Challenges
		Scale of the Statistics
		Pattern Interpretation Challenges
	Arrangements of Challenges
		User Intervention Method
		Probabilistic Method
		Defining and Detecting Anomalies in Human Ecosystems
	Demanding Situations in Managing Huge Records
	Massive Facts Equal Large Possibilities
		Present Answers to Challenges for the Quantity Mission
			Hadoop
			Hadoop-distributed file system
			Hadoop MapReduce
			Apache spark
			Grid computing
			Spark structures
			Capacity solutions for records-variety trouble
		Image Mining and Processing With Big Data
		Potential Answers for Velocity Trouble
			Transactional databases
			Statistics representation
			Massive actualities calculations
			Ability solutions for privateers and safety undertaking
		Ability Solutions for Scalability Assignments
			Big data and cloud computing
			Cloud computing service models
			Answers
			Use record encryption
			Imposing access controls
			Logging
	Discussion
	Conclusion
	Glossary
	References
	Further Reading
3
Big Data Analytics in Healthcare: A Critical Analysis
	Introduction
	Big Data
	Healthcare Data
		Structured Data
		Unstructured Data
		Semistructured Data
		Genomic Data
		Patient Behavior and Sentiment Data
		Clinical Data and Clinical Notes
		Clinical Reference and Health Publication Data
		Administrative and External Data
	Medical Image Processing and its Role in Healthcare Data Analysis
	Recent Works in Big Data Analytics in Healthcare Data
	Architectural Framework and Different Tools for Big Data Analytics in Healthcare Big Data
		Architectural Framework
		Different Tools Used in Big Data Analytics in Healthcare Data
	Challenges Faced During Big Data Analytics in Healthcare
	Conclusion and Future Research
	References
	Further Reading
4
Transfer Learning and Supervised Classifier Based Prediction Model for Breast Cancer
	Introduction
	Related Work
	Dataset and Methodologies
		Convolution Neural Networks (CNNs/ConvNets)
			Transfer learning and convolution networks
			Convolution networks as fixed feature extractors
			Dimensionality reduction and principle component analysis (PCA)
			Supervised machine learning
	Proposed Model
	Implementation
		Feature Extraction
		Dimensionality Reduction
		Classification
		Tuning Hyperparameters of the Classifiers
	Result and Analysis
		10-fold Cross Validation Result
		Magnification Factor Wise Analysis on Validation Accuracy
			Validation accuracy of 40x
			Validation accuracy of 100x
			Validation accuracy of 200x
			Validation accuracy of 400x
			Best validation accuracy
			Performance on the test set
		Result and Analysis of Test Performance
			Test performance on 40x
			Overall performance on 40x
			Test performance on 100x
			Overall performance on 100x
			Test performance on 200x
			Test performance on 400x
			Overall performance on 400x
	Discussion
	Conclusion
	References
	Further Reading
5
Chronic TTH Analysis by EMG and GSR Biofeedback on Various Modes and Various Medical Symptoms Using IoT
	Introduction and Background
		Biofeedback
		Mental Health Introduction
		Importance of Mental Health, Stress, and Emotional Needs and Significance of Study
		Meaning of Mental Health
		Definitions
		Factors Affecting Mental Health
		Models of Stress: Three Models in Practice
			Types of stress
			Causes of stress
			Symptoms of stress
		Big Data and IoT
	Previous Studies (Literature Review)
		Tension Type Headache and Stress
	Independent Variable: Emotional Need Fulfillment
	Meditation-Effective Spiritual Tool With Approach of Biofeedback EEG
		Mind-Body and Consciousness
	Sensor Modalities and Our Approach
		Biofeedback Based Sensor Modalities
		Electromyograph
		Electrodermograph
		Proposed Framework
	Experiments and Results-Study Plot
		Study Design and Source of Data
		Study Duration and Consent From Subjects
		Sampling Design and Allocation Process
		Sample Size
		Study Population
			Inclusion criteria
			Exclusion criteria
		Intervention
		Outcome Parameters
			Primary variables
			Secondary variables
		Analgesic Consumption
		Assessment of Outcome Variables
		Pain Diary
		Data Collection
		Statistical Analysis
		Hypothesis
	Data Collection Procedure-Guided Meditation as per Fig. 5.7G
	Results, Interpretation and Discussion
		The Trend of Average of Frequency
		The Trend of Average of Duration
		The Trend of Average of Intensity
		The Trend of Duration per Cycle With Time
		Trend on Correlation of TTH Duration and Intensity
		Trend on Correlation of TTH Duration With Occurrence
		The Trend of Average of Frequency
		The Trend of Average of Duration
		The Trend of Average of Intensity
		The Trend of Duration per Cycle With Time
		Trend on Correlation of TTH Duration and Intensity
		Trend on Correlation of TTH Duration With Occurrence
		The Trend of Average of Frequency
		The Trend of Average Duration
		The Trend of Average Intensity
		The Trend of Duration per Cycle With Time
		Trend on Correlation of TTH Duration and Intensity
		Trend on Correlation of TTH Duration With Occurrence
		The Trend of Average of Frequency
		The Trend of Average of Duration
		The Trend of Average Intensity
		The Trend of Duration per Cycle With Time
		Trend on Correlation of TTH Duration and Intensity
		Trend on Correlation of TTH Duration With Occurrence
	Findings in This Chapter
	Future Scope, Limitations, and Possible Applications
	Conclusion
		Comprehensive Conclusion
	Acknowledgment
	References
	Further Reading
6
Multilevel Classification Framework of fMRI Data: A Big Data Approach
	Introduction
	Related Work
	Our Approach
		Dataset
		Methodology
		Result Evaluation
		Experimental Results
		Subject-Dependent Experiments on PS+SP
			All features
			ROI-based feature
			Average ROI-based feature
			N-most active-based feature
			N-most active ROI-based feature
		Subject-Dependent Experiment on PS/SP
			ROI-based feature
			Average ROI-based feature
			N-most active-based feature
			Most active ROI-based feature
	Result Analysis
		Summary of the Subject-Dependent Results
		Subject-Independent Experiment
	Conclusion and Future Work
	References
	Further Reading
7
Smart Healthcare: An Approach for Ubiquitous Healthcare Management Using IoT
	Introduction
	Literature Survey
	Proposed Model
		Fetch Module
		Ingest Module
		Retrieve Module
		Act/Notify Module
		Prototype Model of the Proposed Work
	Implementation of the Proposed System
	Simulation and Result Discussion
	Conclusion
	References
8
Blockchain in Healthcare: Challenges and Solutions
	Introduction
		Roadmap
	Healthcare Big Data and Blockchain Overview
		Healthcare Big Data
		Blockchain
		How Blockchain Works
	Privacy of Healthcare Big Data
		Privacy Right by Country and Organization
	How Blockchain Is Applicable for Healthcare Big Data
		Digital Trust
		Intelligent Data Management
		Smart Ecosystem
		Digital Supply Chain
		Cybersecurity
		Interoperability and Data Sharing
		Improving Research and Development (R&D)
		Fighting Counterfeit Drugs
		Collaborative Patient Engagement
		Online Access to Longitudinal Data by Patient
		Off-Chain Data Storage due to Privacy and Data Size
	Blockchain Challenges and Solutions for Healthcare Big Data
		GDPR versus Blockchain
			Problem statement and key factors of GDPR
			Solutions
			Off-chain blockchain advantages
			Off-chain blockchain disadvantages
	Conclusion and Discussion
	References
	Further Reading
9
Intelligence-Based Health Recommendation System Using Big Data Analytics
	Introduction
	Background
		Recommendation System and Its Basic Concepts
		Phases of Recommendation System
		Methodology
			Filtering techniques
			Collaborative-based filtering recommendation system
			Evaluation of recommendation system
	Health Recommendation System
		Designing the Health Recommendation System
		Framework for HRS
		Methods to Design HRS
		Evaluation of HRS
	Proposed Intelligent-Based HRS
		Dataset Description
		Experimental Result Analysis
	Advantages and Disadvantages of the Proposed Health Recommendation System Using Big Data Analytics
	Conclusion and Future Work
	References
	Further Reading
10
Computational Biology Approach in Management of Big Data of Healthcare Sector
	Introduction
	Application of Big Data Analysis
	Database Management System and Next Generation Sequencing (NGS)
	De novo Assembly, Re-Sequencing, Transcriptomics Sequencing and Epigenetics
	Data Collection, Extraction of Genes, and Screening of Drugs
	Different Algorithms Related to Docking
	Molecular Interactions, Scoring Functions, and Discussion of Some Docking Examples
	Conclusions
	Acknowledgments
	References
11
Kidney-Inspired Algorithm and Fuzzy Clustering for Biomedical Data Analysis
	Introduction
	Biological Structure of the Kidney
	Kidney-Inspired Algorithm
	Literature Survey
	Proposed Model
		Fuzzy C-Means Algorithm
		Proposed KA-Based Approach for Biomedical Data Analysis
			Obtaining optimal cluster centers using KA
			Cluster analysis using optimal cluster centers
	Results Analysis
		Evaluation Metrics
		Experimental Results
		Statistical Validity
	Conclusion
	Acknowledgment
	References
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	K
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
	Y
	Z
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