Intelligent Data Analysis for COVID-19 Pandemic (Algorithms for Intelligent Systems)

✍ Scribed by M. Niranjanamurthy (editor), Siddhartha Bhattacharyya (editor), Neeraj Kumar (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 377
• Category: Library

✦ Synopsis

This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.

✦ Table of Contents

Preface
Contents
Editors and Contributors
Machine Learning-Based Ensemble Approach for Predicting the Mortality Risk of COVID-19 Patients: A Case Study
1 Introduction
2 Literature Review
3 Dataset and Methodology Used
3.1 Dataset Description and Preparation
3.2 Data Preprocessing
3.3 Classification and Ensembling Approaches
4 Ensembling Approaches
4.1 Boosting
4.2 Bagging
5 Experiments and Results
5.1 Feature Selection of Patient Attributes
5.2 Performance of Individual Classifiers
6 Conclusion
References
Role of Internet of Health Things (IoHTs) and Innovative Internet of 5G Medical Robotic Things (IIo-5GMRTs) in COVID-19 Global Health Risk Management and Logistics Planning
1 Introduction
1.1 Background of the Study
1.2 Aims and Objective of the Study
2 Literature Review
3 Research Design and Implementation
3.1 Research Analysis
3.2 Research Discussion
4 Future Research Focus
5 Recommendation
6 Conclusion
References
Battling COVID-19 with Process Model of Integrated Digital Technology: An Analysis of Qualitative Data
1 Introduction
2 Research Design and Structure
3 Digital Technology to Combat COVID-19
3.1 Mobile Applications and COVID-19
3.2 Artificial Intelligence, Internet of Things (IoT), Big Data Analytics, and COVID 19
3.3 Social Media and COVID
4 Summarization of Digital Technology Applications and COVID-19
5 Process Model of Integrated Digital Technology
6 Conclusion
References
High-Fidelity Intelligence Ventilator to Help Infect with COVID-19 Based on Artificial Intelligence
1 Introduction
2 Operating and Revision Modes
3 Design and Condition of the Instrument
4 Materials and Technology
4.1 Typical Parts Needed
4.2 Arduino Nano Compatible V3.0 ATmega328
4.3 Electronic Motor Speed Controller
4.4 Wi-Fi Module
5 Results and Discussion
6 Conclusion
References
Boon of Artificial Intelligence in Diagnosis of COVID-19
1 Introduction
2 Novel Coronavirus (SARS-CoV-2)
3 Evolution of Artificial Intelligence
3.1 Strong AI
3.2 Weak AI
4 Applications of Computational Techniques
4.1 Speed Up Diagnosis
4.2 Computerized Tracking
4.3 Tracking of Infected Individual
4.4 Prediction of Incidence Rate and Mortality Rate
4.5 Designing and Development of New Drugs and Vaccines
4.6 Lowering the Work Load
4.7 Prevention of Infectious Disease
5 Traditional Diagnostic Methodology
5.1 Lateral Flow Immunoassay (LFIA)
5.2 Chemiluminescent Immunoassay (CLIA)
5.3 Neutralization Assay
6 Machine Learning
6.1 Algorithms
6.2 Random Forest
7 Contact Tracing
8 Detection Through Smell
9 Conclusion
References
Artificial Intelligence and Big Data Solutions for COVID-19
1 Introduction
2 The COVID-19 Pandemic
3 AI and Big Data Techniques for COVID-19
4 AI and Big Data Applications for COVID-19
4.1 Early Detecting and Finding COVID-19 Cases
4.2 Early Detecting and Finding COVID-19 Cases
4.3 Following Up Contacts
4.4 Projection of Cases and Moralities
4.5 Reducing the Workload on Healthcare Workers
4.6 Prevention of the Infections
5 A Proposed Model of AI and Big Data for COVID-19: Smartphone for Surveillance
6 Discussions
7 Future Insights
8 Conclusions
References
Emerging Trends in Higher Education During Pandemic Covid-19: An Impact Study from West Bengal
1 Introduction
2 Research Background Literature
3 Methodology
3.1 Research Gaps
3.2 Research Objectives
3.3 Sample Design
3.4 Research Approach
3.5 Research Tools Usage in Current Research
3.6 SXUK Case Study Process
4 Research Findings and Discussion
4.1 Teaching–Learning Context During Covid-19
4.2 Content Development Orientation
4.3 ICT Technology Strategies in HEIs
4.4 “Big Five” Strategies
4.5 Technology-CI Adapted Teaching–Learning Strategies
4.6 Higher Educational Institutes Wise
4.7 CI Awareness and Application in HEIs
4.8 Computational Intelligence-ICT Factors Confluence
4.9 CI-Based HEIs Cluster Membership
5 Case Organization: SXUK
5.1 Introduction
5.2 Historical Millstones of SXUK
5.3 SXUK Organogram
5.4 AI-CI Interface Strategies for SXUK
6 Conclusion
References
COVID-19: Virology, Epidemiology, Diagnostics and Predictive Modeling
1 Introduction
2 Virology of SARS-CoV-2
3 Diagnostics and Current Line of Treatment of Coronavirus Disease-2019 (COVID-19)
4 Comparison of Population Distribution of India, USA and Spain
5 Mathematical Modeling
6 Concluding Remarks
References
Improved Estimation in Logistic Regression Through Quadratic Bootstrap Approach: An Application in Indian Agricultural E-learning System During COVID-19 Pandemic
1 Introduction
2 Logistic Regression Model
2.1 Preliminaries
2.2 Identification of the Most Influential Variable
2.3 Estimation in Logistic Regression Model
2.4 Goodness of Fit
2.5 Predictive Ability
2.6 Comparison Measures
3 Empirical Results
3.1 Data and Implementation
3.2 Comparative Assessment Between MLE and Quadratic Bootstrap Estimation
3.3 Outcomes of the Simulation Study
4 Conclusion
References
COVID-19 and Stock Markets: Deaths and Strict Policies
1 Introduction
2 COVID-19 and Its Macroeconomic Effects
3 COVID-19 and Stock Markets
4 Data and Econometric Model
4.1 Diagnostic Statistics and Correlation Analysis
4.2 Analysis Results
5 Conclusion
References
Artificial Intelligence Techniques in Medical Imaging for Detection of Coronavirus (COVID-19/SARS-COV-2): A Brief Survey
1 Introduction
2 Literature Survey
3 Artificial Intelligence
4 Machine Learning
5 Neural Networks
5.1 Deep Learning
5.2 Transfer Learning
5.3 Convolutional Neural Networks
6 CNN Algorithms and Methods Used in the Survey
6.1 Inception V3
6.2 ResNet-50
6.3 Inception-ResNet-v2
6.4 VGG-19
6.5 MobileNet
7 Materials and Methods
7.1 Dataset
7.2 Performance Analysis Parameters
8 Results and Discussions
9 Conclusion and Future Challenges
References
A Travelling Disinfection-Man Problem (TDP) for COVID-19: A Nonlinear Binary Constrained Gaining-Sharing Knowledge-Based Optimization Algorithm
1 Coronavirus (COVID-19): An Overview
2 Coronavirus Decontamination Planning Process
3 Coronavirus Travelling Disinfection-Man Problem (TDP)
4 The Travelling Salesman Problem (TSP) and Its Variations
5 Mathematical Model Formulation for the Travelling Disinfection-Man Problem
6 Real Application Case Study Application: Ain Shams University, Cairo
7 Artificial Intelligence Techniques in Optimization
8 Proposed Methodology
8.1 Overview of Gaining-Sharing Knowledge-Based Optimization Algorithm (GSK)
8.2 Discrete Binary Gaining-Sharing Knowledge-Based Optimization Algorithm (DBGSK)
9 Experimental Results
10 Conclusions
11 Points for Future Researches
References
COVID-19 Lock Down Impact on Mental Health: A Cross-Sectional Online Survey from Kerala, India
1 Introduction
1.1 Motivation for Doing the Research
2 Review of Literature
3 Methods
4 Results and Discussions
4.1 Types of Activities
4.2 Mental Health Issues and Eating Behaviour
4.3 Awareness Among People
5 Conclusion
References
Analysis, Modelling and Prediction of COVID-19 Outbreaks Using Machine Learning Algorithms
1 Introduction
2 COVID-19 Around the Global
3 Machine Learning and Its Types
3.1 Supervised Learning
4 Implementation
4.1 Evaluation Metrics
5 Time Series Data set
5.1 Analysis, Modelling and Prediction of COVID-19
5.2 Confirmed Cases and Death Cases as on 20 July 2020—World
5.3 Confirmed Cases and Death Cases as on 20th July 2020–India
5.4 Model of Machine Learning Algorithm
5.5 Predicting the Outgrowth in the Next 3 Months–India
6 Conclusion
References
Tracking and Analysis of Corona Disease Using Intelligent Data Analysis
1 Introduction
2 AI Versus COVID-19
2.1 Prediction and Data Sharing
2.2 R&D Sector
2.3 Deception
2.4 Monitoring
2.5 Data Overload
2.6 Arrangement of Automated Vehicles
2.7 Variances Between the AI Techniques [1]
3 Using AI to Detect, Respond, and Recover from COVID-19
3.1 Computer-Based Intelligence for COVID-19 Medical Response
4 AI for COVID-19 Social Control
4.1 Man-Made Reasoning in the Battle Against COVID-19
4.2 Information Access
4.3 Security Ensuring Applications
5 How Artificial Intelligence Applications can Contain Coronavirus COVID-19
5.1 Man-Made Reasoning in the Battle Against COVID-19
5.2 Information Access
5.3 Security Ensuring Applications
6 Conclusion
References
Index