Jodi L. Feinberg¹, Frank Cecchin^1,2, Arianna Gonzalez¹, Emily Johnson², Dan G. Halpern^1,*

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 >

Bingjie Yan¹, Jun Wang¹, Zhen Zhang², Xiangyan Tang^{1, *}, Yize Zhou¹, Guopeng Zheng¹, Qi Zou¹, Yao Lu¹, Boyi Liu³, Wenxuan Tu⁴, Neal Xiong⁵

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1473-1490, 2020, DOI:10.32604/cmc.2020.011317

Abstract New coronavirus disease (COVID-19) has constituted a global pandemic and has spread to most countries and regions in the world. Through understanding the development trend of confirmed cases in a region, the government can control the pandemic by using the corresponding policies. However, the common traditional mathematical differential equations and population prediction models have limitations for time series population prediction, and even have large estimation errors. To address this issue, we propose an improved method for predicting confirmed cases based on LSTM (Long-Short Term Memory) neural network. This work compares the deviation between the experimental results of the improved LSTM… More >

Hengyang Lu^{1, *}, Yutong Lou², Bin Jin², Ming Xu²

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1453-1471, 2020, DOI:10.32604/cmc.2020.011270

Abstract Starting from late 2019, the new coronavirus disease (COVID-19) has become a global crisis. With the development of online social media, people prefer to express their opinions and discuss the latest news online. We have witnessed the positive influence of online social media, which helped citizens and governments track the development of this pandemic in time. It is necessary to apply artificial intelligence (AI) techniques to online social media and automatically discover and track public opinions posted online. In this paper, we take Sina Weibo, the most widely used online social media in China, for analysis and experiments. We collect… More >

Xiaorui Zhang^{1, 2, *}, Wenfang Zhang¹, Wei Sun², Tong Xu¹, Sunil Kumar Jha³

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1435-1452, 2020, DOI:10.32604/cmc.2020.011359

Abstract In the current dire situation of the corona virus COVID-19, remote consultations were proposed to avoid cross-infection and regional differences in medical resources. However, the safety of digital medical imaging in remote consultations has also attracted more and more attention from the medical industry. To ensure the integrity and security of medical images, this paper proposes a robust watermarking algorithm to authenticate and recover from the distorted medical images based on regions of interest (ROI) and integer wavelet transform (IWT). First, the medical image is divided into two different parts, regions of interest and non-interest regions. Then the integrity of… More >

Yixian Zhang¹, Jieren Cheng^{2, *}, Yifan Yang², Haocheng Li², Xinyi Zheng², Xi Chen², Boyi Liu³, Tenglong Ren⁴, Naixue Xiong⁵

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1415-1434, 2020, DOI:10.32604/cmc.2020.011316

Abstract With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions. We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining. A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed. Establish a “Scrapy-Redis-Bloomfilter” distributed crawler framework to collect data. The system can judge the positive and negative emotions of the reviewer based on the comments, and can also reflect the… More >

Ramazan Ünlü¹, Ersin Namlı^{2, *}

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 >

Mohammad Shorfuzzaman^{1, *}, 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 >

Muhammad Adnan Khan^{1, *}, 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 >

Rashid Iqbal Khan^1,*, 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 >

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 >