Bo Wang^1,*, Yongxin Zhang¹, Shihui Ji², Binbin Zhang¹, Xiangyu Wang¹, Jiyong Zhang¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3625-3642, 2023, DOI:10.32604/cmc.2023.036754

Abstract A model that can obtain rapid and accurate detection of coronavirus disease 2019 (COVID-19) plays a significant role in treating and preventing the spread of disease transmission. However, designing such a model that can balance the detection accuracy and weight parameters of memory well to deploy a mobile device is challenging. Taking this point into account, this paper fuses the convolutional neural network and residual learning operations to build a multi-class classification model, which improves COVID-19 pneumonia detection performance and keeps a trade-off between the weight parameters and accuracy. The convolutional neural network can extract the COVID-19 feature information by… More >

Hassam Tahir¹, Muhammad Shahbaz Khan¹, Fawad Ahmed², Abdullah M. Albarrak³, Sultan Noman Qasem³, Jawad Ahmad^4,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3517-3535, 2023, DOI:10.32604/cmc.2023.035410

Abstract The COVID-19 outbreak began in December 2019 and was declared a global health emergency by the World Health Organization. The four most dominating variants are Beta, Gamma, Delta, and Omicron. After the administration of vaccine doses, an eminent decline in new cases has been observed. The COVID-19 vaccine induces neutralizing antibodies and T-cells in our bodies. However, strong variants like Delta and Omicron tend to escape these neutralizing antibodies elicited by COVID-19 vaccination. Therefore, it is indispensable to study, analyze and most importantly, predict the response of SARS-CoV-2-derived t-cell epitopes against Covid variants in vaccinated and unvaccinated persons. In this… More >

Mohsin Ghani, Ghulam Gilanie^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2835-2847, 2023, DOI:10.32604/iasc.2023.034857

Abstract The lungs are the main fundamental part of the human respiratory system and are among the major organs of the human body. Lung disorders, including Coronavirus (Covid-19), are among the world’s deadliest and most life-threatening diseases. Early and social distance-based detection and treatment can save lives as well as protect the rest of humanity. Even though X-rays or Computed Tomography (CT) scans are the imaging techniques to analyze lung-related disorders, medical practitioners still find it challenging to analyze and identify lung cancer from scanned images. unless COVID-19 reaches the lungs, it is unable to be diagnosed. through these modalities. So,… More >

Jiaji Wang^1,#, Shuwen Chen^1,2,3,#,*, Yu Cao^1,#, Huisheng Zhu¹, Dimas Lima^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2595-2616, 2023, DOI:10.32604/cmes.2023.025804

Abstract This paper presents a 6-layer customized convolutional neural network model (6L-CNN) to rapidly screen out patients with COVID-19 infection in chest CT images. This model can effectively detect whether the target CT image contains images of pneumonia lesions. In this method, 6L-CNN was trained as a binary classifier using the dataset containing CT images of the lung with and without pneumonia as a sample. The results show that the model improves the accuracy of screening out COVID-19 patients. Compared to other methods, the performance is better. In addition, the method can be extended to other similar clinical conditions. More >

SUBHASH CHANDRA^1,2, SANTWANA PALAI³, EDINARDO FAGNER FERREIRA-MATIAS⁴, IVO CAVALCANTE PITA-NETO⁴, CíCERO LUCAS GOMES-RAMALHO⁴, EDLANE MARTINS DE ANDRADE⁴, RAY SILVA DE ALMEIDA⁵, MARCELLO IRITI^6,7,*, HENRIQUE DOUGLAS MELO-COUTINHO^5,*

BIOCELL, Vol.47, No.4, pp. 677-695, 2023, DOI:10.32604/biocell.2023.026081

Abstract Indian medicinal plants are referred to as the “nectar of life” owing to their phytochemicals and bioactive complexes that are beneficial in treating diseases. Coronavirus disease 2019 (COVID-19) is a global health issue without any proper medication. The indigenous plants of India can be exploited to control the precise signs of SARS-CoV-2. The Ministry of AYUSH (Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy) has advised routine usage of medicinal plants for COVID-19. Medicinal plants like Zingiber officinalis, Azadirachta indica, Ocimum sanctum, Nigella sativa, Withania somnifera, Curcuma longa, Piper nigrum, Allium sativum, Tinospora cordifolia, etc. have immunity-boosting, antiviral, antibacterial, antioxidant… More >

Heesup Han¹, Hong Ngoc Nguyen², Hyerin Lee³, Sanghyeop Lee^4,*

International Journal of Mental Health Promotion, Vol.25, No.4, pp. 449-469, 2023, DOI:10.32604/ijmhp.2023.025379

Abstract Since the outbreak of COVID-19, tourists have been increasingly concerned over various risks of international travel, while knowledge of the pandemic appears to vary significantly. In addition, as travel restrictions continue to impact adversely on international tourism, tourism efforts should be placed more on the domestic markets. Via structural equation modeling, this study unearthed different risk factors impacting Korean travelers’ choices of alternative local destinations in the post-pandemic era. In addition, this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19, which was proven to hold a significantly superior explanatory power of tourists’… More >

Regina Lai-Tong Lee^1,2,*, Anson Chiu-Yan Tang³, Ho-Yu Cheng¹, Connie Yuen-Yu Chong¹, Wilson Wai-San Tam⁴, Wai-Tong Chien¹, Sally Wai-Chi Chan⁵

International Journal of Mental Health Promotion, Vol.25, No.3, pp. 327-342, 2023, DOI:10.32604/ijmhp.2022.026388

Abstract The present study aimed to examine work environment related factors and frontline primary healthcare professionals’ mental-emotional wellbeing during the COVID-19 pandemic in school communities of Hong Kong. A total of 61 (20%) school health nurses (frontline primary healthcare professionals) participated in a cross-sectional online survey from March to June 2020. Outcomes of mental-emotional health were measured using the Mental Health Continuum-Short Form (14-item scale with three subscales related to emotional, social and psychological wellbeing); the Perceived Stress Scale (10-item scale with two subscales related to perceived helplessness and lack of self-efficacy; and the Coping Orientation to Problems Experienced Inventory (Brief… More >

Yun-Jung Choi¹, Youn-Joo Um^2,*

International Journal of Mental Health Promotion, Vol.25, No.3, pp. 421-431, 2023, DOI:10.32604/ijmhp.2023.023255

Abstract Major media outlets have run many articles on the COVID-19 pandemic. Since the public suffers cognitive and emotional effects related to COVID-19 from such reports, we analyzed and reviewed the topics of news reports. We searched newspaper articles with the term ‘COVID-19’ term in four Korean daily newspapers from January 20, 2020, when the first patient in Korea was found, to June 15, 2020. Topic modeling analysis was conducted through text mining using R. Five themes were found: “Changes in people’s everyday life,” “Socio-economic shock,” “Trends in infection,” “Role of the government and business,” and “Increased psychological anxiety,” which all… More >

Basanta Kumar Swain¹, Mohammad Zubair Khan^2,*, Chiranji Lal Chowdhary³, Abdullah Alsaeedi⁴

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2337-2349, 2023, DOI:10.32604/csse.2023.036192

Abstract This research is focused on a highly effective and untapped feature called gammatone frequency cepstral coefficients (GFCC) for the detection of COVID-19 by using the nature-inspired meta-heuristic algorithm of deer hunting optimization and artificial neural network (DHO-ANN). The noisy crowdsourced cough datasets were collected from the public domain. This research work claimed that the GFCC yielded better results in terms of COVID-19 detection as compared to the widely used Mel-frequency cepstral coefficient in noisy crowdsourced speech corpora. The proposed algorithm's performance for detecting COVID-19 disease is rigorously validated using statistical measures, F1 score, confusion matrix, specificity, and sensitivity parameters. Besides,… More >

Abdullah S. AL-Malaise AL-Ghamdi^1,2,3, Sultanah M. Alshammari^3,4, Mahmoud Ragab^3,5,6,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1863-1877, 2023, DOI:10.32604/csse.2023.035869

Abstract Notwithstanding the religious intention of billions of devotees, the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most attendees ignored preventive measures, namely maintaining physical distance, practising hand hygiene, and wearing facemasks. Wearing a face mask in public areas protects people from spreading COVID-19. Artificial intelligence (AI) based on deep learning (DL) and machine learning (ML) could assist in fighting covid-19 in several ways. This study introduces a new deep learning-based Face Mask Detection in Religious Mass Gathering (DLFMD-RMG) technique during the… More >