COVID-19: Prediction, Decision-Making, and its Impacts

✍ Scribed by K.C. Santosh; Amit Joshi

• Publisher: Springer Singapore
• Year: 2020
• Tongue: English
• Leaves: 141
• Series: Lecture Notes on Data Engineering and Communications Technologies, 60
• Category: Library

✦ Synopsis

This book outlines artificial intelligence for COVID-19 issues that are ranging from prediction to decision-making for healthcare support in human lives. Starting with major COVID-19 issues and challenges, it takes possible AI-based solutions for multiple problems, such as early prediction, its role for public health, detection of positive cases, drug analysis, and healthcare support. It mainly employs publicly available data (population) to predict who should be tested for COVID-19, for example, radiological image data to detect COVID-19 positive cases from other similar and/or different manifestations, such as pneumonia, distributed healthcare support, and supply chains in the middle of COVID-19 pandemic. The book includes recently developed AI-driven tools and techniques, such as pattern recognition, anomaly detection, machine learning, and data analytics. It covers a wide range of audience from computer science and engineering to healthcare professionals.

✦ Table of Contents

Preface
Contents
Editors and Contributors
Artificial Intelligence (AI) Joins the Fight Against COVID-19
1 Introduction
2 Main Applications of AI in the COVID-19 Pandemic
2.1 Smart Screening for High Body Temperature
2.2 Surveillance
2.3 Monitoring Treatment
2.4 Multi-purpose Platforms
2.5 Treatments and Cures
2.6 Drug Development and Design
3 Major AI-Driven Tools
3.1 Active Learning (AL)
3.2 Cross-Population Train/Test AI-Driven Models
4 The Future of Artificial Intelligence (AI)
5 Conclusions
References
AI for Covid-19: Conduits for Public Health Surveillance
1 Introduction
2 Data Modelling and Public Health Responses
2.1 Public Health Surveillance and Artificial Intelligence
3 Contact Tracing—The Next Mile
4 Conclusions
References
A Pre-screening Approach for COVID-19 Testing Based on Belief Rule-Based Expert System
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Signs and Symptoms
4 Method
5 Prediction of COIVD-19 Using BRBES
6 Architecture and Implementation of BRBES
7 Representation of Knowledge Database
8 Interface to Gather Symptoms
9 Results and Discussion
10 Conclusion
References
Local Analytical System for Early Epidemic Detection
1 Introduction
2 Related Works
3 The Setup Process of an Analytical System
4 Analytical Operations and the Findings
5 Conclusions
References
Implementing Early Detection System for Covid-19 Using Anomaly Detection
1 Introduction
2 Learning from Outbreak
2.1 Key Concepts in the Area of Infectious Disease Outbreak
2.2 Syndromic Measures Used for Early Detection
3 Anomaly Detection for Early Detection
3.1 Applicability of Anomaly Detection
3.2 Estimation of Useful Models for Anomaly Detection
3.3 Application of Anomaly Detection in Covid-19-Like Diseases
4 Detection System Implementation
4.1 Possible Practical System to Place in Action
4.2 Role of a Successful Early Detection System in the Community
5 Conclusions
References
Covid-19 Classification Based on Gray-Level Co-occurrence Matrix and Support Vector Machine
1 Introduction
2 Dataset
3 Methodology
3.1 Gray-Level Co-occurrence Matrix
3.2 Support Vector Machine
4 Experiments and Results
4.1 Data Acquisition
4.2 Histogram Equalization
4.3 Feature Extraction
4.4 Classification
5 Conclusion
References
Rough Sets in COVID-19 to Predict Symptomatic Cases
1 Introduction
2 Preliminaries
2.1 Rough Sets
2.2 COVID-19
3 Problem Statement
4 Design of Proposed Method Based on Rough Sets
5 Results and Discussions
6 Conclusion
References
COVID-19 Detection via Wavelet Entropy and Biogeography-Based Optimization
1 Introduction
2 Dataset
2.1 K-Fold Cross-Validation
3 Methodology
3.1 Wavelet Entropy
3.2 Biogeography-Based Optimization
4 Experiments, Results and Discussion
5 Conclusion
References
Machine Learning in Fighting Pandemics: A COVID-19 Case Study
1 Introduction
2 Vulnerability Assessment
3 Patient Screening
4 Drug Development
5 Conclusions
References
Healthcare Robots to Combat COVID-19
1 Introduction
2 Next-Generation Smart Healthcare
3 Robot and Its Design Consideration
4 Robots in Healthcare
4.1 Robots for Surgery
4.2 Rehabilitation and Assistive Robots
4.3 Acceptability of Robot for Healthcare
5 Robots in Pandemics
5.1 Robots for COVID-19 Screening
5.2 Robots for Disinfecting Hospital
5.3 Robot for COVID-19 Awareness
5.4 Robots for Assistance in Hospital Logistics
6 Conclusion
References
COVID-19: A Necessity for Changes and Innovations
1 Introduction
2 Structure of Coronavirus
3 COVID-19 Tracking
4 AI-Driven Tools for COVID-19 Prediction and Screening
5 Publicly Available Datasets
6 Socio-Economic Impact and Emotions
7 Conclusion
References
Prediction to Service Delivery: AI in Action
1 Introduction
2 Prediction
3 Logistics Management
3.1 Supply Chain Management
3.2 Autonomous Vehicles for Logistics and Shipping Management
4 Service Delivery
4.1 Best Practices of Education 4.0 During the Pandemic
4.2 Pivotal Role of AI in Education 4.0
References
COVID-19 Impacts Construction Industry: Now, then and Future
1 Introduction
2 Impacts of COVID-19 in Construction Sector
3 Risk Assessment
4 Safety Management for Restarting Work After Post Lockdown at Site
4.1 Guidelines on Work Restart
4.2 Guidelines on the Entry of Construction Site
4.3 Guidelines on Labor Protection
4.4 Guidelines On-Site Hygiene
4.5 Guidelines on Labor Camp
4.6 Guidelines on Contractors and Staffs
5 Future Construction Industry Technologies
6 Discussions
7 Conclusion
References
COVID-19 on Air Quality Index (AQI): A Necessary Evil?
1 Introduction
2 Related Works
3 Air Quality Index and Its Variation in Lockdown
3.1 Effect on Air Quality of Different Countries in COVID-19 Crisis
4 Reflections
References