Call for Chapters

Submissions are closed. Thanks for the great interest in the project for fighting against COVID-19!

Data Science for COVID-19

Edited by Utku Kose, Deepak Gupta, Victor Hugo C. de Albuquerque, Ashish Khanna 

to be published by Elsevier

COVID-19 is currently the most dangerous variation of the coronavirus as threating the humankind, accepted as the pandemic by the World Health Organization (WHO). Nowadays, there is not almost any country where issues regarding COVID-19 is not observed. With thousands of reported deaths and the cases more than that, the world is in an active war to eliminate that virus. In the past, such situation had already been experienced with important viruses such as Ebola, H1N1, and Influenza. However, the most devastating results within last two centuries may will be associated with the active COVID-19. While the sub-fields medical as well as natural sciences have been working instantly on deriving solutions and trying to protect the humankind against such virus types, there is also a great focus on technological developments for improving the mechanism – momentum of science for effective and efficient solutions. At this point, Data Science is the most powerful tools for researchers to fight against COVID-19. Thanks to instant data-analyze and predictive techniques by the Data Science, it is possible to get positive results and introduce revolutionary solutions against the related medical diseases. By running capabilities – resources for rising the Data Science, technological fields like Artificial Intelligence (with Machine / Deep Learning), Data Mining, Applied Mathematics are essential components for processing data, recognizing patterns, modeling new techniques and improving the advantages of the Data Science more. Nowadays, there is a great interest in application potentials of the Data Science so that it will be an effective approach for taking the humankind more step away, after COVID-19 and also before pandemics similar to the COVID-19 many appear.

The main goal of the proposed edited book: ‘Data Science for COVID-19’ is to provide the most recent research and innovative developments regarding the COVID-19. In this context, the book aims to inform the target audience about the latest findings-results regarding a wide variety of Data Science applications for fighting COVID-19.

There is currently a great emergency state in all over the world and the scientific audience is looking for instant solutions and further works to eliminate all cases of COVID-19 problems and similar pandemics that may threaten the humankind in the future. Moving from that, alternative applications of Data Science are too valuable and critical. Such applications can be done over data such as medical image, raw data, statistical findings, and even ongoing real-time rates in terms of active pandemic cases, deaths, treated people and potential components such as animals as the origin of such pandemics.

Submission Guidelines

All submissions should be done by email to: utkukose@gmail.com and / or deepakgupta@mait.ac.in and / or victor.albuquerque@unifor.br and / or ashishkhanna@mait.ac.in

All papers must be original and not simultaneously submitted to another book project, journal or conference. The following important dates will be considered for the submissions:

• Full Paper Submission: 30.04.2020
• Notification of Accept / Reject: 05.05.2020
• Final Chapter Due: 10.05.2020 
• (you may ask to the editors for pre-proposal and full chapter preparation documents. Please track this page for further updates regarding submission procedures.)

List of Topics (as not limited to)

• COVID-19 virus with their essentials as a threat,
• Image Analysis and Processing for COVID-19,
• Design of Cognition and Computing for COVID-19,
• Data Processing for COVID-19,
• Geoprocessing / Tracking for COVID-19,
• Diagnosis for COVID-19,
• Laboratorial Data Analysis for COVID-19,
• Predictive Systems for COVID-19,
• Mobile technology solutions for COVID-19,
• Artificial Intelligence based solutions for COVID-19,
• Treatment of for COVID-19 with Data Science,
• Public Safety for COVID-19,
• Governmental Applications for COVID-19,
• Data Science Policies for COVID-19,
• Internet of Health Things (IoHT) for COVID-19,
• Big Data for COVID-19,
• New Data Models for COVID-19,
• ...etc.

It is important that research works with only targeting COVID-19 will be given more emphasis while a few of alternative works giving insights for potential pandemics will be accepted. Also, the contributors will be encouraged to provide also success stories, negative results and experiences / feedback they received from physicians and medical staff.

Desired Main Chapters / Parts for the Flow of the Table of Contents:

• Introduction to Data Science for COVID-19: This chapter provides general information about how Data Science can be applied in the context of fighting against COVID-19 and pandemics. In detail, the chapter considers what are pandemics, past and present of the COVID-19 and the related coronavirus variations, past information regarding similar diseases (such as Ebola, H1N1, Influenza). Later the chapter discusses essential methods and future insights in the context of Data Science.
• Image Analysis and Data Processing for COVID-19: The chapter focuses on how to perform data processing over especially image data for diagnosing COVID-19, treating it and for further investigations as well predictive analyzes. As the analysis of medical image is also critical, the chapter will give more emphasis on how to diagnose COVID-19. On the other hand, the chapter considers also possible medical data for diagnosis.
• Geoprocessing / Tracking for COVID-19: The chapter gives importance to how geoprocessing is effective and critical in detecting / tracking COVID-19, predicting its flow over the world, via moves by both humans and animals. In detail, the chapter discusses also computer-oriented geoprocessing solutions in this manner as well future insights, advantages – disadvantages and open gaps, limitations in terms of Data Science applications.
• Predictive Systems for COVID-19: The chapter provides a general view for predictive systems to be used against COVID-19. In detail, use of Data Science as well as active role of Artificial Intelligence (Machine / Deep Learning) oriented solutions are evaluated. Furthermore, chapter also gives a wide variety of information for building future generation systems, medical test kits for real-time, early predictive solutions for giving enough time to the humankind for having necessary pre-cautions including medical, economical, and sociological strategies.
• Design Cognition and Computing for COVID-19: This chapter provides an overview of the design cognition and design computing fields with applications in COVID-19, presenting cognitive studies and protocols on designing or design education, the role of drawings, the behavior of the brain and also social behavior in design. Computational social science of the topic is addressed, namely cognition-based agents to study interactions in individuals, teams and organizations and computational models of creative design, analogy, emergence and situated agents. Evolutionary systems in design and ontologies also are discussed.
• Mobile Technology Solutions for COVID-19: The chapter gives emphasis on mobile technology, which is an essential component of our life. In this context, the chapter discusses how the power of mobile technology can be used against the treat of COVID-19, evaluates mobile applications (informative, test-oriented, geo-tracking based…etc.) developed to be used for keeping the public informed against COVID-19, potential problems, and keeping the balance of the life in the time of COVID-19. Furthermore, the chapter explains how Data Science is applied within mobile technologies (in terms of communication protocols, hardware – software solutions...etc.) for better solution ways against COVID-19.
• Artificial Intelligence Based Solutions for COVID-19: The chapter considers the Artificial Intelligence, as a strong solution tool within the field of medical, to be used in the context of fighting against the COVID-19. The chapter focuses both Machine Learning and Deep Learning techniques as effective tools for intelligent recognition, predictive analyzes and even deep transformation of medical data to get effective and efficient tools against COVID-19. The chapter also considers the intelligent systems as drug – vaccine discovery tools, robust techniques to work over big data for saving time and resources while dealing with the COVID-19.
• Treatment for COVID-19 with Data Science: This chapter considers possible applications of Data Science for effective treatment of COVID-19. In detail, discoveries of innovative treatment methods, techniques and their effective uses are widely explained and evaluated in detail. The chapter also provides present-past experiences, and even future insights to fight with the best capabilities and resources as well as data, for eliminating COVID-19 and potential pandemics.
• Public Safety for COVID-19: The chapter explains how well public safety can be ensured with applications by Data Science as it has great advantages of analyzing different amount of data effectively, ensuring accurate use of resources, enabling well being of the public at the time of COVID-19. In detail, the chapter also includes a wide overview of current public safety strategies and future applications based on active use of Data Science oriented algorithms and techniques.
• IoHT for COVID-19: This chapter considers the Internet of Health Things (IoHT) as the powerful technology for enabling a collaborative, efficient use of medical devices (and even daily life devices to support medical devices) for timely dealing with COVID-19 cases, performing effective diagnosis tests, instant treatments and enabling pre-cautions as well as running informative communication technologies on the background and causing all the necessary vital resources to be used accurately for keeping the humankind strong enough COVID-19 or potential pandemics.
• Big Data for COVID-19: This chapter takes the concept of Big Data as the essential component of Data Science for ensuring better development and research against the COVID-19. As the current technological era requires careful analyze of Big Data, rise of COVID-19 and the appeared problems can be associated with the not enough use of effective solutions. At this point, previously experiences – observed signs of the danger state can be effectively analyzed with Data Science so that this chapter provides information, recent research flow and the future insights about that scope.
• New Data Models for COVID-19: The chapter focuses on more use of Mathematics / Applied Mathematics and any potential analytical techniques to derive new data models for understanding characteristics of the COVID-19. In this way, alternative further applications to treat COVID-19 or at least lowering its side-effects can be designed accordingly. As the life itself can be defined with the nature of Mathematics, role of data models and potential new types of data models will be discussed – evaluated widely for contributing to research regarding the COVID-19.
• ...etc.

Editors

• Utku Kose, PhD. (Suleyman Demirel University, Turkey)
• Deepak Gupta, PhD. (Maharaja Agrasen Institute of Technology, India)
• Victor Hugo C. de Albuquerque (Universidade de Fortaleza, Brazil)
• Ashish Khanna, PhD. (Maharaja Agrasen Institute of Technology, India)

Publication

'Data Science for COVID-19' will be published by Elsevier.

Contact

All questions about submissions should be e-mailed to: utkukose@gmail.com