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  • Open Access

    ARTICLE

    Machine Learning and Classical Forecasting Methods Based Decision Support Systems for COVID-19

    Ramazan Ünlü1, Ersin Namlı2, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1383-1399, 2020, DOI:10.32604/cmc.2020.011335

    Abstract From late 2019 to the present day, the coronavirus outbreak tragically affected the whole world and killed tens of thousands of people. Many countries have taken very stringent measures to alleviate the effects of the coronavirus disease 2019 (COVID-19) and are still being implemented. In this study, various machine learning techniques are implemented to predict possible confirmed cases and mortality numbers for the future. According to these models, we have tried to shed light on the future in terms of possible measures to be taken or updating the current measures. Support Vector Machines (SVM), Holt-Winters, Prophet, and Long-Short Term Memory… More >

  • Open Access

    ARTICLE

    On the Detection of COVID-19 from Chest X-Ray Images Using CNN-Based Transfer Learning

    Mohammad Shorfuzzaman1, *, Mehedi Masud1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1359-1381, 2020, DOI:10.32604/cmc.2020.011326

    Abstract Coronavirus disease (COVID-19) is an extremely infectious disease and possibly causes acute respiratory distress or in severe cases may lead to death. There has already been some research in dealing with coronavirus using machine learning algorithms, but few have presented a truly comprehensive view. In this research, we show how convolutional neural network (CNN) can be useful to detect COVID-19 using chest X-ray images. We leverage the CNN-based pre-trained models as feature extractors to substantiate transfer learning and add our own classifier in detecting COVID-19. In this regard, we evaluate performance of five different pre-trained models with fine-tuning the weights… More >

  • Open Access

    ARTICLE

    Intelligent Forecasting Model of COVID-19 Novel Coronavirus Outbreak Empowered with Deep Extreme Learning Machine

    Muhammad Adnan Khan1, *, Sagheer Abbas2, Khalid Masood Khan1, Mohammad A. Al Ghamdi3, Abdur Rehman2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1329-1342, 2020, DOI:10.32604/cmc.2020.011155

    Abstract An epidemic is a quick and widespread disease that threatens many lives and damages the economy. The epidemic lifetime should be accurate so that timely and remedial steps are determined. These include the closing of borders schools, suspension of community and commuting services. The forecast of an outbreak effectively is a very necessary but difficult task. A predictive model that provides the best possible forecast is a great challenge for machine learning with only a few samples of training available. This work proposes and examines a prediction model based on a deep extreme learning machine (DELM). This methodology is used… More >

  • Open Access

    REVIEW

    Plant Derived Antiviral Products for Potential Treatment of COVID-19: A Review

    Rashid Iqbal Khan1,*, Mazhar Abbas1, Khurram Goraya2, Muhammad Zafar-ul-Hye3, Subhan Danish3

    Phyton-International Journal of Experimental Botany, Vol.89, No.3, pp. 438-452, 2020, DOI:10.32604/phyton.2020.010972

    Abstract COVID-19 caused by SARS-CoV-2 is declared global pandemic. The virus owing high resemblance with SARS-CoV and MERS-CoV has been placed in family of beta-coronavirus. However, transmission and infectivity rate of COVID-19 is quite higher as compared to other members of family. Effective management strategy with potential drug availability will break the virus transmission chain subsequently reduce the pressure on the healthcare system. Extensive research trials are underway to develop novel efficient therapeutics against SARS-CoV-2. In this review, we have discussed the origin and family of coronavirus, structure, genome and pathogenesis of virus SARS-CoV-2 inside human host cell; comparison among SARS,… More >

  • Open Access

    ARTICLE

    Why Ignore the Dark Side of Social Media? A Role of Social Media in Spreading Corona-Phobia and Psychological Well-Being

    Saqib Amin*

    International Journal of Mental Health Promotion, Vol.22, No.1, pp. 29-38, 2020, DOI:10.32604/IJMHP.2020.011115

    Abstract Coronaviruses are a category of associated viruses that trigger disease in mammals and birds. Human coronaviruses have been identified including severe acute respiratory syndrome-related coronavirus (SARS-CoV) in 2003, human coronavirus NL63 (HCoV NL63) in 2004, human coronavirus HKU1 (HKU1) in 2005, Middle East respiratory syndrome-related coronavirus (MERSCoV) in 2012, and severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) in December, 2019. This study aims to examine whether social media at residing/admittance in quarantine ward (due to corona virus pandemic disease) affects psychological health or not? We asked questions from 250 quarantined patients infected from coronavirus (restricted to quarantine ward) about their psychological… More >

  • Open Access

    ARTICLE

    Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity

    Xiangao Jiang1, Megan Coffee2, 3, *, Anasse Bari4, *, Junzhang Wang4, Xinyue Jiang5, Jianping Huang1, Jichan Shi1, Jianyi Dai1, Jing Cai1, Tianxiao Zhang6, Zhengxing Wu1, Guiqing He1, Yitong Huang7

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 537-551, 2020, DOI:10.32604/cmc.2020.010691

    Abstract The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel disease and b) resource limitations… More >

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