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  • 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 >

  • Open Access

    ARTICLE

    A Stochastic Model to Assess the Epidemiological Impact of Vaccine Booster Doses on COVID-19 and Viral Hepatitis B Co-Dynamics with Real Data

    Andrew Omame1,2,*, Mujahid Abbas3,6, Dumitru Baleanu4,5,6

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2973-3012, 2024, DOI:10.32604/cmes.2023.029681

    Abstract A patient co-infected with COVID-19 and viral hepatitis B can be at more risk of severe complications than the one infected with a single infection. This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19. The model is fitted to real COVID-19 data from Pakistan. The proposed model incorporates logistic growth and saturated incidence functions. Rigorous analyses using the tools of stochastic calculus, are performed to study appropriate conditions for the existence of unique global solutions, stationary distribution in the sense of ergodicity and disease… More >

  • Open Access

    ARTICLE

    Serial Multiple Mediation of the Relationship between Positive Coping Style and Post-Traumatic Growth among Chinese College Students in the Aftermath of COVID-19

    Qi Li, Jinsheng Hu*, Peng Wan

    International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1173-1186, 2023, DOI:10.32604/ijmhp.2023.030343

    Abstract

    Given the ongoing character of COVID-19, higher-education students encountered multifaceted pressures brought about by the pandemic and had to overcome many difficulties during this period. Accordingly, it is imperative to identify the factors that may have protective effects on the social functioning and mental status of college students in the aftermath of COVID-19. This cross-sectional study sought to ascertain the internal mechanism of positive coping (PC) styles affecting post-traumatic growth (PTG) and considered the mediating roles of cognitive reappraisal (CR), psychological resilience (PR), and deliberate rumination (DR), which are essential for understanding how and to what extent these factors shaped… More >

  • Open Access

    REVIEW

    Molecular basis of COVID-19, ARDS and COVID-19-associated ARDS: Diagnosis pathogenesis and therapeutic strategies

    PRIYADHARSHINI THANJAVUR SRIRAMAMOORTHI1,2, GAYATHRI GOPAL1,2, SHIBI MURALIDAR1,2, SAI RAMANAN ESWARAN1,2, DANUSH NARAYAN PANNEERSELVAM1,2, BHUVANESWARAN MEIYANATHAN1,2, SRICHANDRASEKAR THUTHIKKADU INDHUPRAKASH1,2, SENTHIL VISAGA AMBI1,2,*

    BIOCELL, Vol.47, No.11, pp. 2335-2350, 2023, DOI:10.32604/biocell.2023.029379

    Abstract The novel coronavirus pneumonia (COVID-19) is spreading worldwide and threatening people greatly. The routes by which SARS-CoV-2 causes lung injury have grown to be a major concern in the scientific community since patients with new Coronavirus, severe acute respiratory syndrome coronavirus (SARS-CoV-2) have a high likelihood of developing acute respiratory distress syndrome (ARDS) in severe cases. The mortality rate of COVID-19 has increased over the period due to rapid spread, and it becomes crucial to understand the disease epidemiology, pathogenic mechanisms, and suitable treatment strategies. ARDS is a respiratory disorder and is one of the clinical manifestations observed in patients… More > Graphic Abstract

    Molecular basis of COVID-19, ARDS and COVID-19-associated ARDS: Diagnosis pathogenesis and therapeutic strategies

  • Open Access

    ARTICLE

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

    Shaik Mahaboob Basha1,*, Victor Hugo C. de Albuquerque2, Samia Allaoua Chelloug3,*, Mohamed Abd Elaziz4,5,6,7, Shaik Hashmitha Mohisin8, Suhail Parvaze Pathan9

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1981-2004, 2024, DOI:10.32604/cmes.2023.031425

    Abstract Manual investigation of chest radiography (CXR) images by physicians is crucial for effective decision-making in COVID-19 diagnosis. However, the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning techniques. This study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies, including normal cases. Texture information is extracted using gray co-occurrence matrix (GLCM)-based features, while vessel-like features are obtained using Frangi, Sato, and Meijering filters. Machine learning models employing Decision Tree (DT) and Random Forest (RF) approaches are designed to categorize CXR images into common lung infections, lung… More > Graphic Abstract

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

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