Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,

Persuasion is an indispensable skill in everyday life; that is why, it has aroused researchers’ interest. This study aims to investigate the most frequently used persuasive strategies in texting WHO COVID-19 Virtual Press Conferences and explore how these strategies are employed to achieve persuasive messages.To this end, a text of WHO COVID-19 Virtual Press Conferences has been chosen randomly to be analyzed based on Dillard and Shen’s (2013) “Persuasive strategies in Health Campaigns”. A qualitative method has been adopted in analyzing the selected data to investigate the credibility and validity of the persuasive strategies used in such a domain. Findings have shown that most of the persuasive appeals based on the adopted mode

Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.

This study aimed to evaluate the effect of the COVID-19 outbreak on emergencies and pain among orthodontic patients attending a teaching hospital. The study was conducted among orthodontic patients receiving active orthodontic treatment or in a retention period at the College of Dentistry, University of Baghdad, Iraq. Their participation was voluntary, and they filled out an Arabic-translated questionnaire. The survey included general information, orthodontic problems, and a numerical rating scale for pain assessment. We used descriptive and inferential statistics (frequencies and intersecting frequencies), chi-square test and linear regression. Out of 75 orthodontic patients, only 54 (15 males and 39 females) were included in the s

The objective of this study is to ascertain the pivotal role of headlines in captivating viewers' attention toward news bulletins. Additionally, it aims to explore the factors that contribute to the correlation between headlines and the public's acceptance or rejection of the meticulously crafted news articles presented through these bulletins. The study delves into the mechanisms employed in writing and editing headlines, focusing on their style, expert composition, and intriguing nature. These factors inevitably influence the level of acceptance and engagement of the viewership with the news articles disseminated via the news bulletins. Employing a descriptive methodology, the researcher distributed 200 question

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

In this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which

Coronavirus disease 2019 (COVID-19) is a flu-like infection caused by a novel virus known as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). After the widespread around the world, it was announced by the World Health Organization (WHO) as a global pandemic. The symptoms of COVID-19 may arise within 2 weeks and the severity ranged from mild with signs of respiratory infection to severe cases of organ failure and even death. Management of COVID-19 patients includes supportive treatment and pharmacological medications expected to be effective with no definitive cure of the disease. The aims of this study are highlighting the management protocol and supportive therapy especially vitamin D and manifesting the clinical symptoms b

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models