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  • Open Access

    ARTICLE

    Analysis of Twitter Data Using Evolutionary Clustering during the COVID-19 Pandemic

    Ibrahim Arpaci1, Shadi Alshehabi2, Mostafa Al-Emran3, *, Mahmoud Khasawneh4, Ibrahim Mahariq4, Thabet Abdeljawad5, 6, 7, Aboul Ella Hassanien8, 9

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 193-204, 2020, DOI:10.32604/cmc.2020.011489

    Abstract People started posting textual tweets on Twitter as soon as the novel coronavirus (COVID-19) emerged. Analyzing these tweets can assist institutions in better decision-making and prioritizing their tasks. Therefore, this study aimed to analyze 43 million tweets collected between March 22 and March 30, 2020 and describe the trend of public attention given to the topics related to the COVID-19 epidemic using evolutionary clustering analysis. The results indicated that unigram terms were trended more frequently than bigram and trigram terms. A large number of tweets about the COVID-19 were disseminated and received widespread public attention during the epidemic. The high-frequency… More >

  • Open Access

    ARTICLE

    Managing the Adult Congenital Heart Disease Patient in the COVID-19 Pandemic—A New York Perspective

    Jodi L. Feinberg1, Frank Cecchin1,2, Arianna Gonzalez1, Emily Johnson2, Dan G. Halpern1,*

    Congenital Heart Disease, Vol.15, No.3, pp. 141-146, 2020, DOI:10.32604/CHD.2020.012039

    Abstract Adults with congenital heart disease (ACHD) are likely at increased risk for complications of COVID-19. ACHD centers should prepare to deliver routine cardiac care and support for patients with COVID-19 safely at home, as the number of COVID-19 infections worldwide continues to increase. This brief report aims to share the strategies we have used in our ACHD program to manage and treat our patients during this global health crisis at one of the initial epicenters of the pandemic in New York City, and offer suggestions for preparation for ACHD clinicians. More >

  • Open Access

    ARTICLE

    Mathematical Analysis of Novel Coronavirus (2019-nCov) Delay Pandemic Model

    Muhammad Naveed1, Muhammad Rafiq2, Ali Raza3, Nauman Ahmed4, Ilyas Khan5, *, Kottakkaran Sooppy Nisar6, Atif Hassan Soori1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1401-1414, 2020, DOI:10.32604/cmc.2020.011314

    Abstract In this manuscript, the mathematical analysis of corona virus model with time delay effect is studied. Mathematical modelling of infectious diseases has substantial role in the different disciplines such as biological, engineering, physical, social, behavioural problems and many more. Most of infectious diseases are dreadful such as HIV/AIDS, Hepatitis and 2019-nCov. Unfortunately, due to the non-availability of vaccine for 2019- nCov around the world, the delay factors like, social distancing, quarantine, travel restrictions, holidays extension, hospitalization and isolation are used as key tools to control the pandemic of 2019-nCov. We have analysed the reproduction number RnCov of delayed model. Two… More >

  • Open Access

    ARTICLE

    Data Driven Modelling of Coronavirus Spread in Spain

    G. N. Baltas1, *, F. A. Prieto1, M. Frantzi2, C. R. Garcia-Alonso1, P. Rodriguez1, 3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1343-1357, 2020, DOI:10.32604/cmc.2020.011243

    Abstract During the late months of last year, a novel coronavirus was detected in Hubei, China. The virus, since then, has spread all across the globe forcing Word Health Organization (WHO) to declare COVID-19 outbreak a pandemic. In Spain, the virus started infecting the country slowly until rapid growth of infected people occurred in Madrid, Barcelona and other major cities. The government in an attempt to stop the rapssid spread of the virus and ensure that health system will not reach its capacity, implement strict measures by putting the entire country in quarantine. The duration of these measures, depends on the… 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

    Updated thoughts on SARS-CoV-2 and coronavirus therapies, fighting and surviving

    WENJUAN LI*, GE SONG

    BIOCELL, Vol.44, No.2, pp. 127-135, 2020, DOI:10.32604/biocell.2020.010018

    Abstract From late December 2019 a new human-adapted coronavirus, SARS-CoV-2, was observed and isolated in clustered patients in Wuhan, China. It has been proved to be able to transmit human-to-human and cause pneumonia, leading to about 2% fatality. Its genome characteristics, immune responses and related potential treatments, such as chemical drugs, serum transfusion and vaccines including DNA vaccines, are discussed in this review for a brief summary. 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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