Mohammad Mehedi Hassan^1,*, 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 - 11 March 2024

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… More >

S. Dickson¹, S. Padmasekaran¹, Pushpendra Kumar^2,*, 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 - 11 March 2024

Abstract This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQI_cRVW 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 More >

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 - 08 March 2024

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… More >

Rong Fu^*, Luze Xie

International Journal of Mental Health Promotion, Vol.26, No.1, pp. 21-30, 2024, DOI:10.32604/ijmhp.2023.041730 - 05 February 2024

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… More >

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

BIOCELL, Vol.48, No.1, pp. 1-8, 2024, DOI:10.32604/biocell.2023.031158 - 30 January 2024

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… More >

Mohamed Abdel-Basset¹, Hossam Hawash¹, Mohamed Abouhawwash^2,3,*, S. S. Askar⁴, Alshaimaa A. Tantawy¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1171-1187, 2024, DOI:10.32604/cmc.2023.044425 - 30 January 2024

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… More >

Andrew Omame^1,2,*, Mujahid Abbas^3,6, Dumitru Baleanu^4,5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2973-3012, 2024, DOI:10.32604/cmes.2023.029681 - 15 December 2023

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 More >

Shaik Mahaboob Basha^1,*, Victor Hugo C. de Albuquerque², Samia Allaoua Chelloug^3,*, Mohamed Abd Elaziz^4,5,6,7, 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 - 17 November 2023

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… More > Graphic Abstract

Muhammad Farman^1,2,4, Ali Akgül^3,9,*, Mir Sajjad Hashemi⁵, Liliana Guran^6,7, Amelia Bucur^8,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1385-1403, 2024, DOI:10.32604/cmes.2023.028803 - 17 November 2023

Abstract New fractional operators, the COVID-19 model has been studied in this paper. By using different numerical techniques and the time fractional parameters, the mechanical characteristics of the fractional order model are identified. The uniqueness and existence have been established. The model’s Ulam-Hyers stability analysis has been found. In order to justify the theoretical results, numerical simulations are carried out for the presented method in the range of fractional order to show the implications of fractional and fractal orders. We applied very effective numerical techniques to obtain the solutions of the model and simulations. Also, we… More >

Elias Hossain¹, Abdullah Alshahrani², Wahidur Rahman^3,*

Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 109-123, 2023, DOI:10.32604/iasc.2022.029511 - 05 February 2024

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)… More >