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Understanding COVID-19: The Role of Computational Intelligence

  • Book
  • © 2022

Overview

Editors:
  1. Janmenjoy Nayak

    1. Department of Computer Science & Engineering, Aditya Institute of Technology and Management (AITAM) (An Autonomous Institution), Srikakulam, India

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  2. Bighnaraj Naik

    1. Department of Computer Application, Veer Surendra Sai University of Technology, Burla, India

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  3. Ajith Abraham

    1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, USA

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  • Presents advanced computational intelligence approaches spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, self-organizing systems, fuzzy systems, and hybrid intelligent systems in solving COVID-19
  • Covers novel computational intelligence and technological models for the purpose of effective COVID-19 solving at par with the standards laid down by the World Health Organization
  • Written by experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 963)

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Table of contents (23 chapters)

  1. Front Matter

    Pages i-xv
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  2. Learning from Various Modalities of COVID-19 Data

    1. Front Matter

      Pages 1-1
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    2. COVID-19 Pandemic: Theory, Concepts and Challenges

      • Anindya Banerjee, Raj krishan Ghosh, Surajit Basak, Arijit Dey
      Pages 3-29

    3. Evolutionary Algorithm Based Summarization for Analyzing COVID-19 Medical Reports

      • Chirantana Mallick, Sunanda Das, Asit Kumar Das
      Pages 31-58

    4. Chest CT in COVID-19 Pneumonia: Potentials and Limitations of Radiomics and Artificial Intelligence

      • Federica Vernuccio, Giuseppe Cutaia, Roberto Cannella, Laura Vernuccio, Roberto Lagalla, Massimo Midiri
      Pages 59-76

    5. Use of Deep Learning Based Frameworks on Pixel Scaled Images of Chest CT Scans for Detection of COVID-19

      • Sushant Shetty, Amit Gawade, Subodh Deolekar
      Pages 77-99

    6. SARS-CoV-2 Infection and Antibody-Dependent Enhancement

      • Aliye Bastug, Hurrem Bodur
      Pages 101-113

    7. Graph-Based Clustering Algorithm for Social Community Transmission Control of COVID-19 During Lockdown

      • Varun Nagesh Jolly Behera, Ashish Ranjan, Motahar Reza
      Pages 115-139

    8. COVID-19 Recommendation System of Chest X-Ray Images Using CNN Deep Learning Technique with Optimizers and Activation Functions

      • Niyati Sinha, Puhup Karjee, Riddhi Agrawal, Ankita Banerjee, Chittaranjan Pradhan
      Pages 141-163

    9. Application of Deep Learning Techniques for COVID-19 Management

      • Rajan Gupta, Anshuman Gupta, Manan Bedi, Saibal K. Pal
      Pages 165-197

  3. Prediction and Risk Analysis of COVID-19 Susceptibility

    1. Front Matter

      Pages 199-199
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    2. An Exploratory Study of Disaster Risk Management Mobile Applications in Pandemic Periods

      • K Saravanan, K. Ramesh, V. Sri Vigna Hema, S. Viganesh
      Pages 201-223

    3. Potential of Deep Learning Algorithms in Mitigating the Spread of COVID-19

      • Oluwafemi A. Sarumi, Ons Aouedi, Lawan J. Muhammad
      Pages 225-244

    4. Predicting Antiviral Drugs for COVID-19 Treatment Using Artificial Intelligence Based Approach

      • Ayan Banerjee, Soumen Kumar Pati
      Pages 245-269

    5. Geographic Spread and Control of 2019-nCoV in the Absence of Vaccine

      • Himadri Shekhar Mondal, Motahar Reza, Prasanta Sahoo
      Pages 271-290

    6. Machine Learning Based Anxiety Prediction of General Public from Tweets During COVID-19

      • Shubham Tribedi, Anuraag Biswas, Swarup Kr Ghosh, Anupam Ghosh
      Pages 291-312

    7. A Role of Emerging Technologies in the Design of Novel Framework for COVID-19 Data Analysis and Decision Support System

      • S. Rama Krishna, Mohammad Sirajuddin
      Pages 313-337

    8. Gaussian Regression Models for Day-Level Forecasting of COVID-19 in European Countries

      • Umut Özkaya, Åžaban Öztürk
      Pages 339-356

    9. Computational Intelligence Based Hybrid Hyperparameter Tuned Prediction Techniques for COVID-19 Epidemiological Data

      • S. Dhamodharavadhani, R. Rathipriya
      Pages 357-375

  4. Combating COVID-19 with Advanced Computational Intelligence Techniques

    1. Front Matter

      Pages 377-377
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Keywords

About this book

This book provides a comprehensive description of the novel coronavirus infection, spread analysis, and related challenges for the effective combat and treatment. With a detailed discussion on the nature of transmission of COVID-19, few other important aspects such as  disease symptoms, clinical application of radiomics, image analysis, antibody treatments, risk analysis, drug discovery, emotion and sentiment analysis, virus infection, and fatality prediction are highlighted. The main focus is laid on different issues and futuristic challenges of computational intelligence techniques in solving and identifying the solutions for COVID-19. The book drops radiance on the reasons for the growing profusion and complexity of data in this sector. Further, the book helps to focus on further research challenges and directions of COVID-19 for the practitioners as well as researchers. 

Editors and Affiliations

  • Department of Computer Science & Engineering, Aditya Institute of Technology and Management (AITAM) (An Autonomous Institution), Srikakulam, India

    Janmenjoy Nayak

  • Department of Computer Application, Veer Surendra Sai University of Technology, Burla, India

    Bighnaraj Naik

  • Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, USA

    Ajith Abraham

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