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  • Open Access

    ARTICLE

    Approach for Training Quantum Neural Network to Predict Severity of COVID-19 in Patients

    Engy El-shafeiy1, Aboul Ella Hassanien2, Karam M. Sallam3,*, A. A. Abohany4

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1745-1755, 2021, DOI:10.32604/cmc.2020.013066

    Abstract Currently, COVID-19 is spreading all over the world and profoundly impacting people’s lives and economic activities. In this paper, a novel approach called the COVID-19 Quantum Neural Network (CQNN) for predicting the severity of COVID-19 in patients is proposed. It consists of two phases: In the first, the most distinct subset of features in a dataset is identified using a Quick Reduct Feature Selection (QRFS) method to improve its classification performance; and, in the second, machine learning is used to train the quantum neural network to classify the risk. It is found that patients’ serial blood counts (their numbers of… More >

  • Open Access

    ARTICLE

    Intelligent Decision Support System for COVID-19 Empowered with Deep Learning

    Shahan Yamin Siddiqui1,2, Sagheer Abbas1, Muhammad Adnan Khan3,*, Iftikhar Naseer4, Tehreem Masood4, Khalid Masood Khan3, Mohammed A. Al Ghamdi5, Sultan H. Almotiri5

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1719-1732, 2021, DOI:10.32604/cmc.2020.012585

    Abstract The prompt spread of Coronavirus (COVID-19) subsequently adorns a big threat to the people around the globe. The evolving and the perpetually diagnosis of coronavirus has become a critical challenge for the healthcare sector. Drastically increase of COVID-19 has rendered the necessity to detect the people who are more likely to get infected. Lately, the testing kits for COVID-19 are not available to deal it with required proficiency, along with-it countries have been widely hit by the COVID-19 disruption. To keep in view the need of hour asks for an automatic diagnosis system for early detection of COVID-19. It would… More >

  • Open Access

    ARTICLE

    A Hybrid Deep Learning Model for COVID-19 Prediction and Current Status of Clinical Trials Worldwide

    Shwet Ketu*, Pramod Kumar Mishra

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1896-1919, 2021, DOI:10.32604/cmc.2020.012423

    Abstract Infections or virus-based diseases are a significant threat to human societies and could affect the whole world within a very short time-span. Corona Virus Disease-2019 (COVID-19), also known as novel coronavirus or SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus-2), is a respiratory based touch contiguous disease. The catastrophic situation resulting from the COVID-19 pandemic posed a serious threat to societies globally. The whole world is making tremendous efforts to combat this life-threatening disease. For taking remedial action and planning preventive measures on time, there is an urgent need for efficient prediction models to confront the COVID-19 outbreak. A deep learning-based ARIMA-LSTM hybrid… More >

  • Open Access

    ARTICLE

    Analysis and Dynamics of Fractional Order Mathematical Model of COVID-19 in Nigeria Using Atangana-Baleanu Operator

    Olumuyiwa J. Peter1, Amjad S. Shaikh2,*, Mohammed O. Ibrahim1, Kottakkaran Sooppy Nisar3, Dumitru Baleanu4,5,6, Ilyas Khan7, Adesoye I. Abioye1

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1823-1848, 2021, DOI:10.32604/cmc.2020.012314

    Abstract We propose a mathematical model of the coronavirus disease 2019 (COVID-19) to investigate the transmission and control mechanism of the disease in the community of Nigeria. Using stability theory of differential equations, the qualitative behavior of model is studied. The pandemic indicator represented by basic reproductive number R0 is obtained from the largest eigenvalue of the next-generation matrix. Local as well as global asymptotic stability conditions for the disease-free and pandemic equilibrium are obtained which determines the conditions to stabilize the exponential spread of the disease. Further, we examined this model by using Atangana–Baleanu fractional derivative operator and existence criteria… More >

  • Open Access

    ARTICLE

    Performance Estimation of Machine Learning Algorithms in the Factor Analysis of COVID-19 Dataset

    Ashutosh Kumar Dubey1,*, Sushil Narang1, Abhishek Kumar1, Satya Murthy Sasubilli2, Vicente García-Díaz3

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1921-1936, 2021, DOI:10.32604/cmc.2020.012151

    Abstract Novel Coronavirus Disease (COVID-19) is a communicable disease that originated during December 2019, when China officially informed the World Health Organization (WHO) regarding the constellation of cases of the disease in the city of Wuhan. Subsequently, the disease started spreading to the rest of the world. Until this point in time, no specific vaccine or medicine is available for the prevention and cure of the disease. Several research works are being carried out in the fields of medicinal and pharmaceutical sciences aided by data analytics and machine learning in the direction of treatment and early detection of this viral disease.… More >

  • Open Access

    ARTICLE

    Is Social Distancing, and Quarantine Effective in Restricting COVID-19 Outbreak? Statistical Evidences from Wuhan, China

    Salman A. Cheema1, Tanveer Kifayat2, Abdu R. Rahman2, Umair Khan3, A. Zaib4, Ilyas Khan5,*, Kottakkaran Sooppy Nisar6

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1977-1985, 2021, DOI:10.32604/cmc.2020.012096

    Abstract The flow of novel coronavirus (COVID-19) has affected almost every aspect of human life around the globe. Being the emerging ground and early sufferer of the virus, Wuhan city-data remains a case of multifold significance. Further, it is of notable importance to explore the impact of unique and unprecedented public health response of Chinese authorities—the extreme lockdown of the city. In this research, we investigate the statistical nature of the viral transmission concerning social distancing, extreme quarantine, and robust lockdown interventions. We observed highly convincing and statistically significant evidences in favor of quarantine and social distancing approaches. These findings might… More >

  • Open Access

    ARTICLE

    Qualitative Analysis of a Fractional Pandemic Spread Model of the Novel Coronavirus (COVID-19)

    Ali Yousef1,*, Fatma Bozkurt1,2, Thabet Abdeljawad3,4,5

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 843-869, 2021, DOI:10.32604/cmc.2020.012060

    Abstract In this study, we classify the genera of COVID-19 and provide brief information about the root of the spread and the transmission from animal (natural host) to humans. We establish a model of fractional-order differential equations to discuss the spread of the infection from the natural host to the intermediate one, and from the intermediate one to the human host. At the same time, we focus on the potential spillover of bat-borne coronaviruses. We consider the local stability of the co-existing critical point of the model by using the Routh–Hurwitz Criteria. Moreover, we analyze the existence and uniqueness of the… More >

  • Open Access

    ARTICLE

    Nonlinear Time Series Analysis of Pathogenesis of COVID-19 Pandemic Spread in Saudi Arabia

    Sunil Kumar Sharma1, Shivam Bhardwaj2,*, Rashmi Bhardwaj3, Majed Alowaidi1

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 805-825, 2021, DOI:10.32604/cmc.2020.011937

    Abstract This article discusses short–term forecasting of the novel Corona Virus (COVID-19) data for infected and recovered cases using the ARIMA method for Saudi Arabia. The COVID-19 data was obtained from the Worldometer and MOH (Ministry of Health, Saudi Arabia). The data was analyzed for the period from March 2, 2020 (the first case reported) to June 15, 2020. Using ARIMA (2, 1, 0), we obtained the short forecast up to July 02, 2020. Several statistical parameters were tested for the goodness of fit to evaluate the forecasting methods. The results show that ARIMA (2, 1, 0) gave a better forecast… More >

  • Open Access

    ARTICLE

    Hospital Bed Allocation Strategy Based on Queuing Theory during the COVID-19 Epidemic

    Jing Hu1, Gang Hu2,*, Jiantao Cai3, Lipeng Xu2, Qirun Wang4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 793-803, 2021, DOI:10.32604/cmc.2020.011110

    Abstract During the current epidemic, it is necessary to ensure the rehabilitation treatment of children with serious illness. At the same time, however, it is essential to effectively prevent cross-infection and prevent infections from occurring within the hospital setting. To resolve this contradiction, the rehabilitation department of Nanjing Children’s Hospital adjusted its bed allocation based on the queuing model, with reference to the regional source and classification of the children’s conditions in the rehabilitation department ward. The original triple rooms were transformed into a double room to enable the treatment of severely sick children coming from other places. A M/G/2 queuing… More >

  • Open Access

    ARTICLE

    Potential Inhibitory Effect of Vitamins Against COVID-19

    Kashaf Junaid1,*, Sumera Qasim2, Humaira Yasmeen3, Hasan Ejaz1, Abdullah Alsrhani1, Muhammad Ikram Ullah1, Fahad Ahmad4, Abdul Rehman5

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 707-714, 2021, DOI:10.32604/cmc.2020.012976

    Abstract Coronavirus disease 2019 (COVID-19) is a current pandemic that has affected more than 195 countries worldwide. In this severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, when treatment strategies are not yet clear and vaccines are not available, vitamins are an excellent choice to protect against this viral infection. The rationale behind this study was to examine the inhibitory effect of vitamins B, C, and D against the main protease of SARSCoV-2 and angiotensin-converting enzyme 2 (ACE2), which have critical rolesin the immune system. Molecular docking, performed by using MOE-Dock of the Chemical Computing Group, was used to understand the… More >

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