Academia Open Vol 8 No 2 (2023): December DOI: 10.21070/acopen.8.2023.8087 . Article type: (Medicine)Impact of COVID-19 on Dental Students' Psychological Health Maryam Hameed Alwan, [email protected], (1) Department of Oral Diagnosis, College of Dentistry, Baghdad University, Iraq, Iraq (1) Corresponding author Abstract This study investigates the psychological impact of the COVID-19 pandemic on dental students at Baghdad University College of Dentistry. Conducted between December 2021 and January 2022, this cross-sectional survey aligns with ethical guidelines and the Helsinki Declaration. The study utilized Cochran's equation to determine a sample size of at least 400, ensuring a 95% confidence level with a 5% margin of e

Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

The possible effects of COVID-19 vaccines on reproductive health and male fertility in particular have been discussed intensely by the scientific community and the public since their introduction during the pandemic. On news outlets and social media platforms, many claims have been raised regarding the deleterious effects of COVID-19 vaccines on sperm quality without scientific evidence. In response to this emerging conflict, we designed this study to evaluate and assess the effect of the Pfizer-BioNTech mRNA COVID-19 vaccine on male fertility represented by the semen analysis parameters.

     In this paper, a novel coronavirus (COVID-19) model is proposed and investigated. In fact, the pandemic spread through a close contact between infected people and other people but sometimes the infected people could show two cases; the first is symptomatic and the other is asymptomatic (carrier) as the source of the risk. The outbreak of Covid-19 virus is described by a mathematical model dividing the population into four classes. The first class represents the susceptible people who are unaware of the disease. The second class refers to the susceptible people who are aware of the epidemic by media coverage. The third class is the carrier individuals (asymptomatic) and the fourth class represents the infected ind

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

       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

Background: Lymphomas are group of diseases caused by malignant lymphocytes that accumulate in lymph nodes and caused the characteristics lymphadenopathy. Occasionally, they may spill over into blood or infiltrate organs outside the lymphoid tissue. The major subdivision of lymphomas is into Hodgkin lymphoma and non–Hodgkin lymphoma and this is based on the histologic presence of Reed-Sternberg cells in Hodgkin lymphoma. Salivary immunoglobulin A is the prominent immunoglobulin and is considered to be the main specific defense mechanism in oral cavity. The aim of this study was to determine the level of salivary immunoglobulin A in lymphoma patients before and after chemotherapy treatment. Subjects, materials and methods: The study i