Special lssues
Table of Content

Big Data, Analytics and Intelligent Algorithms for COVID-19

Submission Deadline: 10 September 2020 (closed)

Guest Editors

Prof. Ravi Samikannu, Botswana International University of Science and Technology, Botswana.
Dr. Karthikrajan Senthilnathan, Revoltaxe India Private Limited, Chennai, India.
Dr. Sampath Kumar Venkatachary, Grant Thornton, Botswana.
Dr. Srinivasan Murugesan, Kongu Engineering College, India.
Dr. Sivaram Murugan, Lebanese French University, Iraq.


The world faced different types of epidemic in the past decades. Even from the December 2019 the world facing a new epidemic COVID-19. The situation report given by World Health Organization (WHO) says globally 7533177 confirmed COVID-19 cases and 422770 deaths as of June 13th, 2020. The total new cases in the last 24 hours are 122667 confirmed cases and 4476 deaths. The number   of affected cases on COVID-19 and death will be expected to continue more.


Over the past decade the data creation is increasing exponentially. The collection of data, technology and methodologies called as Big Data. The effective decision making can be achieved when analysis the data. The data collection is analyzed interpretation and communication of meaningful patterns. Intelligent algorithms interact with the environment intelligently. Big data and Intelligent algorithms combine can accomplish complex tasks beyond the human skills. Both can collect the data, organize and analyze the data, large varied data sets to create the patterns. This pattern can help to address the different problems which are able to give solutions to the COVID-19 issue. The offering solutions can predict and prevention of the spread of diseases. The best solutions can be provided with the help of the Big Data.


It is important to make the availability of data and access the data from anywhere with the global collaboration with more security. Artificial intelligence help to give high performance solutions, running big data directly from the enterprise storage etc., The aim of this special issue proposal is to invite researchers to contribute papers to create effective methods and tools can help to track the spread of the COVID-19 disease and to determine the prediction of the spread of the virus. The different methods to prevent the pandemic and to stop further spreading. The theoretical studies and practical applications are welcome for submission. This special issue can be a forum for the researchers from all over the world to present their work related to COVID-19. 


• COVID-19 analysis using Big Data
• COVID-19 analysis using pattern recognition
• Medical imaging using computer vision for COVID-19
• Artificial technique analysis for COVID-19
• Machine learning techniques and analysis for COVID-19
• Information Technology participation in Patient monitoring and tracking for COVID-19
• Medical Management system for COVID-19
• Treatment simulation model and analysis for COVID-19
• Telemedicine system for COVID-19
• Optimal Resource allocation for Epidemic control
• Simulation optimization for epidemic control
• Optimization methods for patient allocation during epidemic
• COVID-19 dynamic optimization model for allocation of medical resources
• Optimizing infectious disease interventions during an emerging epidemic
• Contact tracing by social network analysis using learning techniques
• Risk management for COVID-19
• Optimization control strategies for COVID-19
• Ethical and public policy dimensions for COVID-19
• Cost optimization model for infectious disease with treatment
• Mathematical model of infectious design transmission
• Risk profiling for COVID-19
• Using predictive analysis for health care improvement
• Big data for Predictive analysis for emerging epidemic
• Statistical foundations for COVID-19
• Nonlinear and dynamic programming for epidemic intervention
• Intelligent algorithms and their applications for information security
• Big Data Analytics for prediction and application for COVID-19
• Big data analytics for prediction in medicine and health related applications

Published Papers

  • Open Access


    Survey of Robotics in Education, Taxonomy, Applications, and Platforms during COVID-19

    Hussain A. Younis, A. S. A. Mohamed, R. Jamaludin, M. N. Ab Wahab
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 687-707, 2021, DOI:10.32604/cmc.2021.013746
    (This article belongs to this Special Issue: Big Data, Analytics and Intelligent Algorithms for COVID-19)
    Abstract The coronavirus disease 2019 (COVID-19) is characterized as a disease caused by a novel coronavirus known as severe acute respiratory coronavirus syndrome 2 (SARS-CoV-2; formerly known as 2019-nCoV). In December 2019, COVID-19 began to appear in a few countries. By the beginning of 2020, it had spread to most countries across the world. This is when education challenges began to arise. The COVID-19 crisis led to the closure of thousands of schools and universities all over the world. Such a situation requires reliance on e-learning and robotics education for students to continue their studies to avoid the mingling between people… More >

  • Open Access


    A Comprehensive Investigation of Machine Learning Feature Extraction and Classification Methods for Automated Diagnosis of COVID-19 Based on X-ray Images

    Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Begonya Garcia-Zapirain, Salama A. Mostafa, Mashael S. Maashi, Alaa S. Al-Waisy, Mohammed Ahmed Subhi, Ammar Awad Mutlag, Dac-Nhuong Le
    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3289-3310, 2021, DOI:10.32604/cmc.2021.012874
    (This article belongs to this Special Issue: Big Data, Analytics and Intelligent Algorithms for COVID-19)
    Abstract The quick spread of the Coronavirus Disease (COVID-19) infection around the world considered a real danger for global health. The biological structure and symptoms of COVID-19 are similar to other viral chest maladies, which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 disease. In this study, an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods (e.g., artificial neural network (ANN), support vector machine (SVM), linear kernel and radial basis function (RBF), k-nearest neighbor… More >

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