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Data Science for COVID-19 Volume 1 - 1st Edition - ISBN: 9780128245361, 9780128245378

Data Science for COVID-19 Volume 1

1st Edition

Computational Perspectives

Editors: Utku Kose Deepak Gupta Victor de Albuquerque Ashish Khanna
Paperback ISBN: 9780128245361
eBook ISBN: 9780128245378
Imprint: Academic Press
Published Date: 20th May 2021
Page Count: 752
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Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation.

Key Features

  • Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and treatment of the COVID-19 virus
  • Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings
  • Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers
  • Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions


Academics (scientists, researchers, MSc. PhD. students) from the fields of Computer Science and Engineering, Biomedical Engineering, Biology, Chemistry, Electronics and Communication Engineering, and Information Technology. The audience also includes interested professionals-experts from both public and private industries of medical, computer, data science, information technologies. The book may be used in Data Science, Medical, Biomedical, Artificial Intelligence, Machine Learning, Deep Learning, and even Data (i.e. Image, Signal) Processing oriented courses given at especially Health, Biology, Biomedical Engineering or similar programs of universities, institutions

Table of Contents

  1. Predictive models to the COVID-19
    2. An AI Based Decision Support and Resource Management System for COVID-19 Pandemic
    3. Normalizing Images is Good to Improve Computer-Assisted COVID-19 Diagnosis
    4. Detection and Screening of COVID-19 Through Chest CT Radiographs Using Deep Neural Networks
    5. Differential Evolution to improve the effectiveness of the epidemiological SEIR model enhanced with dynamic social distancing: the case of COVID-19 and Italy
    6. Limitations and Challenges on the Diagnosis of COVID-19 Using Radiology Images and Deep Learning
    7. Deep Convolutional Neural Network Based Image Classification for Covid-19 Diagnosis
    8. Statistical Machine Learning Forecasting Simulation for Discipline Prediction and Cost Estimation of COVID-19 Pandemic
    9. Application of Machine Learning for the Diagnosis of COVID-19
    10. PwCOV in Cluster Based Web Server: An Assessment of Service Oriented Computing for COVID-19 Disease Processing System
    11. COVID-19-affected Medical Image Analysis using Denser Net
    12. uTakeCare: unlock full decentralization of personal data for a respectful decontainment in the context of COVID-19: toward a digitally empowered anonymous citizenship
    13. COVID-19 Detection from Chest X-Rays Using Transfer Learning with Deep CNN
    14. Lexicon Based Sentiment Analysis Using Twitter Data: A Case of COVID-19 Outbreak in India and Abroad
    15. Real time social distancing alerting and contact tracing using image processing
    16. Machine Learning Models for Predicting Survivability in COVID-19 Patients
    17. Robust and Secured Telehealth System for COVID-19 Patients
    18. A Novel Approach to Predict COVID-19 Using Support Vector Machine
    19. An Ensemble Predictive Analytics of Covid-19 Infodemic Tweets Using Bag of Words
    20. Forecast & Prediction of Covid-19 Using Machine Learning
    21. Time Series Analysis of the COVID-19 Pandemic in Australia using Genetic Programming
    22. Image Analysis and Data Processing for COVID-19
    23. A Demystifying Convolutional Neural Networks using Gradcam for Prediction of Coronavirus Disease (Covid-19) On X-Ray Images
    24. Transfer Learning Based Convolutional Neural Network for Covid-19 Detection with X-Ray Images
    25. Computational Modelling of the Pharmacological actions of some anti-viral agents against SARS-CoV-2
    26. Mobile Technology Solutions for COVID-19: RSSI-based COVID-19 mobile app to comply with social distancing using bluetooth signals from smartphones
    27. COVID-19 Pandemic in India: Forecasting Using Machine Learning Techniques
    28. Mathematical Recipe for Curbing Corona Virus (Covid-19) Transmition Dynamics
    29. Sliding Window Time Series Forecasting with Multi-Layer Perceptron and Multi Regression of COVID-19 outbreak in Malaysia
    30. A Two-Level Deterministic Reasoning Pattern to Curb the Spread of Covid-19 in Africa
    31. Data-driven approach to covid-19 infection forecast in Nigeria using negative binomial regression model
    32. A Novel Machine Learning Based Detection and Diagnosis Model for Corona Virus Disease (Covid-19) using Discrete Wavelet Transform (DWT) with Rough Neural Network (RNN)
    33. Artificial Intelligence Based Solutions for Early Identification and Classification of COVID-19 and Acute Respiratory Distress Syndrome
    34. Internet of Medical Things (IoMT) with Machine Learning based COVID-19 Diagnosis Model using Chest X-Ray Images
    35. The growth of COVID-19 in Spain. A view based on time-series forecasting methods
    36. On Privacy Enhancement Using u-Indistinguishability to COVID19 Contact Tracing Approach in Korea
    37. Scheduling Shuttle Ambulance Vehicles for COVID-19 Quarantine Cases, A Multi-objective Multiple 0-1 Knapsack Model with A Novel Discrete Binary Gaining-Sharing knowledge-based Optimization Algorithm


No. of pages:
© Academic Press 2021
20th May 2021
Academic Press
Paperback ISBN:
eBook ISBN:

About the Editors

Utku Kose

Dr. Kose received the BSc. degree from Gazi University, Turkey (2008). He received MSc. degree from Afyon Kocatepe University, Turkey (2010) and PhD. degree from Selcuk University, Turkey (2017). Currently, he is an Associate Professor in Suleyman Demirel University, Turkey. He has more than 100 publications including articles, books, proceedings, and reports. He is also in editorial boards of scientific journals and serves as one of the editors of the Biomedical and Robotics Healthcare book series (CRC Press). His research interest includes artificial intelligence, machine ethics, artificial intelligence safety, optimization, chaos, distance education, e-learning, computer education, and computer science.

Affiliations and Expertise

Associate Professor, Suleyman Demirel University, Turkey

Deepak Gupta

Dr. Gupta is an eminent academician; plays versatile roles and responsibilities within lectures, research, publications, consultancy, and community service. He has 13-years of rich expertise in teaching and two years in the industry with focus on rational-practical learning. He has served as Editor-in-Chief, Guest Editor, Associate Editor in SCI and various reputed journals. He has actively been an organizing end of various reputed international conferences. He has completed Post-Doc. from Inatel, Brazil, and PhD. from Dr. APJ Abdul Kalam Technical University. He authored / edited over 43 books, and published over 144 papers in reputed journals and conferences (including 73 SCI indexed journals). He acts also as faculty resource person, session chair, reviewer, TPC member in FDPs, conferences, and journals..

Affiliations and Expertise

Assistant Professor, Maharaja Agrasen Institute of Technology, India

Victor de Albuquerque

Victor Hugo C. de Albuquerque [M’17, SM’19] is a professor and senior researcher at the University of Fortaleza, LAPISCO/IFCE, and ARMTEC Tecnologia em Robótica, Brazil. He has a Ph.D. in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is an expert in IoT, Machine/Deep Learning, Pattern Recognition, Robotics.

Affiliations and Expertise

Professor and Senior Researcher at the University of Fortaleza, LAPISCO/IFCE, and ARMTEC Tecnologia em Robótica, Brazil

Ashish Khanna

Dr. Ashish Khanna has 16 years of expertise in teaching, entrepreneurship, and research & development. He received his Ph.D. degree from National Institute of Technology, Kurukshetra, India. He has completed his postdoc from Internet of Things Lab at Inatel, Brazil. He has published around 40 SCI indexed papers in IEEE Transaction, Springer, Elsevier, Wiley and many more reputed Journals with cumulative impact factor of above 100. He has around 90 research articles in top SCI/ Scopus journals, conferences and book chapters. He is co-author/editor of numerous books, including Advanced Computational Techniques for Virtual Reality in Healthcare from Springer, Intelligent Data Analysis: From Data Gathering to Data Comprehension from Wiley, and Hybrid Computational Intelligence: Challenges and Applications from Elsevier. His research interests include Distributed Systems, MANET, FANET, VANET, IoT, and Machine Learning. He is one of the founders of Bhavya Publications and Universal Innovator Lab. Universal Innovator is actively involved in research, innovation, conferences, startup funding events and workshops. He is currently working at the Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India and is also a Visiting Professor at the University of Valladolid, Spain.

Affiliations and Expertise

Professor, Maharaja Agrasen Institute of Technology, Delhi, India; Visiting Professor, University of Valladolid, Spain

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