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  • Open Access

    ARTICLE

    Deep Learning-Based Mask Identification System Using ResNet Transfer Learning Architecture

    Arpit Jain1, Nageswara Rao Moparthi1, A. Swathi2, Yogesh Kumar Sharma1, Nitin Mittal3, Ahmed Alhussen4, Zamil S. Alzamil5,*, MohdAnul Haq5

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 341-362, 2024, DOI:10.32604/csse.2023.036973

    Abstract Recently, the coronavirus disease 2019 has shown excellent attention in the global community regarding health and the economy. World Health Organization (WHO) and many others advised controlling Corona Virus Disease in 2019. The limited treatment resources, medical resources, and unawareness of immunity is an essential horizon to unfold. Among all resources, wearing a mask is the primary non-pharmaceutical intervention to stop the spreading of the virus caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) droplets. All countries made masks mandatory to prevent infection. For such enforcement, automatic and effective face detection systems are crucial. This study presents a face… More >

  • Open Access

    ARTICLE

    Transparent and Accurate COVID-19 Diagnosis: Integrating Explainable AI with Advanced Deep Learning in CT Imaging

    Mohammad Mehedi Hassan1,*, Salman A. AlQahtani2, Mabrook S. AlRakhami1, Ahmed Zohier Elhendi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3101-3123, 2024, DOI:10.32604/cmes.2024.047940

    Abstract In the current landscape of the COVID-19 pandemic, the utilization of deep learning in medical imaging, especially in chest computed tomography (CT) scan analysis for virus detection, has become increasingly significant. Despite its potential, deep learning’s “black box” nature has been a major impediment to its broader acceptance in clinical environments, where transparency in decision-making is imperative. To bridge this gap, our research integrates Explainable AI (XAI) techniques, specifically the Local Interpretable Model-Agnostic Explanations (LIME) method, with advanced deep learning models. This integration forms a sophisticated and transparent framework for COVID-19 identification, enhancing the capability of standard Convolutional Neural Network… More >

  • Open Access

    ARTICLE

    A Study on the Transmission Dynamics of the Omicron Variant of COVID-19 Using Nonlinear Mathematical Models

    S. Dickson1, S. Padmasekaran1, Pushpendra Kumar2,*, Kottakkaran Sooppy Nisar3, Hamidreza Marasi4

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2265-2287, 2024, DOI:10.32604/cmes.2023.030286

    Abstract This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models, considering the delay in converting susceptible individuals into infected ones. The significant delays eventually resulted in the pandemic’s containment. To ensure the safety of the host population, this concept integrates quarantine and the COVID-19 vaccine. We investigate the stability of the proposed models. The fundamental reproduction number influences stability conditions. According to our findings, asymptomatic cases considerably impact the prevalence of Omicron infection in the community. The real data of the Omicron variant from Chennai, Tamil Nadu, India, is used to validate the… More >

  • Open Access

    ARTICLE

    Sleep Quality and Emotional Adaptation among Freshmen in Elite Chinese Universities during Prolonged COVID-19 Lockdown: The Mediating Role of Anxiety Symptoms

    Xinqiao Liu*, Linxin Zhang, Xinran Zhang

    International Journal of Mental Health Promotion, Vol.26, No.2, pp. 105-116, 2024, DOI:10.32604/ijmhp.2023.042359

    Abstract Under the effects of COVID-19 and a number of ongoing lockdown tactics, anxiety symptoms and poor sleep quality have become common mental health issues among college freshmen and are intimately related to their emotional adaptation. To explore this connection, this study gathered data from a sample of 256 freshmen enrolled in an elite university in China in September 2022. The association between sleep quality, anxiety symptoms, and emotional adaptation was clarified using correlation analysis. Additionally, the mediating function of anxiety symptoms between sleep quality and emotional adaptation was investigated using a structural equation model. The results reveal that: (1) Chinese… More >

  • Open Access

    ARTICLE

    News Modeling and Retrieving Information: Data-Driven Approach

    Elias Hossain1, Abdullah Alshahrani2, Wahidur Rahman3,*

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 109-123, 2023, DOI:10.32604/iasc.2022.029511

    Abstract This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling. The Methodology of this study is categorized into three phases: the Text Classification Approach (TCA), the Proposed Algorithms Interpretation (PAI), and finally, Information Retrieval Approach (IRA). The TCA reflects the text preprocessing pipeline called a clean corpus. The Global Vectors for Word Representation (Glove) pre-trained model, FastText, Term Frequency-Inverse Document Frequency (TF-IDF), and Bag-of-Words (BOW) for extracting the features have been interpreted in this research. The PAI manifests the Bidirectional Long Short-Term Memory (Bi-LSTM) and Convolutional Neural Network… More >

  • Open Access

    ARTICLE

    Do Public Health Events Promote the Prevalence of Adjustment Disorder in College Students? An Example from the COVID-19 Pandemic

    Rong Fu*, Luze Xie

    International Journal of Mental Health Promotion, Vol.26, No.1, pp. 21-30, 2024, DOI:10.32604/ijmhp.2023.041730

    Abstract COVID-19, as one of the most serious sudden public health problems in this century, is a serious threat to people’s mental health. College students, as a vulnerable group, are more likely to develop mental health problems. When the body is unable to adapt to new changes in the environment, the main mental health problem that arises is adjustment disorder. The aim of this study was to assess the prevalence and influencing factors of adjustment disorder among college students during the COVID-19 outbreak in China. Cross-sectional data collected by web-based questionnaires were obtained through convenience sampling and snowball sampling between March… More >

  • Open Access

    REVIEW

    Extracellular vesicles and angiotensin-converting enzyme 2 in COVID-19 disease

    YU LIU*, ROBERT J. KASPER, NATALIE J. S. CHOI*

    BIOCELL, Vol.48, No.1, pp. 1-8, 2024, DOI:10.32604/biocell.2023.031158

    Abstract Extracellular vesicles (EVs) are membranous vesicular structures released from almost all eukaryotic cell types under different physiological or pathological conditions. Growing evidence demonstrates that EVs can serve as mediators of intercellular communication between donor and recipient cells or microorganism-infected and noninfected cells. Coronavirus disease 2019 (COVID-19) disease is caused by infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of host cells in the respiratory system and various extra-pulmonary tissue/organs, resulting in complications of multiple organ systems. As the cell surface receptor, angiotensin-converting enzyme 2 (ACE2) mediates cellular entry of SARS-CoV-2 into the host cells in patients with COVID-19.… More >

  • Open Access

    ARTICLE

    Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT Scan: From Concepts toward Clinical Explainability

    Mohamed Abdel-Basset1, Hossam Hawash1, Mohamed Abouhawwash2,3,*, S. S. Askar4, Alshaimaa A. Tantawy1

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1171-1187, 2024, DOI:10.32604/cmc.2023.044425

    Abstract The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT scans. This study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 diagnosis. This paper proposes a novel deep learning approach, called Conformer Network, for explainable discrimination of viral pneumonia depending on the lung Region of Infections (ROI) within a single modality radiographic CT scan. Firstly, an efficient U-shaped transformer network is integrated for lung image segmentation. Then, a robust transfer learning technique is introduced to design a robust feature… More >

  • Open Access

    ARTICLE

    Is There a Specific Profile of COVID-19 Risk Perception among People with Cancer? A Cross-Sectional Study

    Existe-t-il un profil spécifique de perception du risque de COVID-19 chez les personnes atteintes d’un cancer ? une étude transversale

    Renaud Mabire-Yon1,*, Arnaud Siméone1, Thibaud Marmorat2, Anne-Sophie Petit1, Mathilde Perray1, Costanza Puppo1, Charlotte Bauquier1, Claire Della Vecchia1, Hervé Picard3, Marie Préau1

    Psycho-Oncologie, Vol.17, No.4, pp. 245-256, 2023, DOI:10.32604/po.2023.042296

    Abstract Aims: This study aimed to determine if people with cancer (PWC) exhibit a unique COVID-19 risk perception profile and identify psychosocial factors characterizing PWC who do not conform to the majority risk perception profile. Procedure: A cross-sectional online self-questionnaire study was conducted in France from April 25 to May 07, 2020, with a sample (n = 748) comprising PWC, individuals not currently receiving cancer treatment, and those without a history of cancer. Latent profiles of COVID-19 risk perception (PCRP) were established. Methods: A multivariate multinomial logistic regression was performed to assess the association between cancer status and PCRP membership. Characteristics… More >

  • Open Access

    REVIEW

    Exosomes in viral infection: Effects for pathogenesis and treatment strategies

    FATEMEH HEIDARI1,2, REIHANEH SEYEDEBRAHIMI1,2, PIAO YANG3, MOHSEN ESLAMI FARSANI1,2, SHIMA ABABZADEH2,4, NASER KALHOR5, HAMED MANOOCHEHRI6, MOHSEN SHEYKHHASAN7,*, MARYAM AZIMZADEH8,9,*

    BIOCELL, Vol.47, No.12, pp. 2597-2608, 2023, DOI:10.32604/biocell.2023.043351

    Abstract Exosomes are small vesicles that carry molecules from one cell to another. They have many features that make them interesting for research, such as their stability, low immunogenicity, size of the nanoscale, toxicity, and selective delivery. Exosomes can also interact with viruses in diverse ways. Emerging research highlights the significant role of exosomes in viral infections, particularly in the context of diseases like COVID-19, HIV, HBV and HCV. Understanding the intricate interplay between exosomes and the human immune system holds great promise for the development of effective antiviral therapies. An important aspect is gaining clarity on how exosomes influence the… More >

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