The aim of the research is to identify the relationship between health anxiety associated with Coronavirus (Covid 19) and its relationship to health behavior among Baghdad University employees, as well as to identify the differences in health anxiety and health behavior according to the variables (gender, occupation, and age). To achieve the objectives of the research, a scale was designed to measure the health anxiety in addition to the adoption of the health behavior scale prepared by (Renner & Schwarzer, 2005). The two scales were applied to a sample of (277) academics and (206) employees, while the number of students was (667). The sample was chosen by electronic application from a number of colleges at Al-Jadiriyah Complex. Afte

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), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

Vaccination is a vital cornerstone of public health, which has saved countless lives throughout history. Therefore, achieving high vaccination uptake rates is essential for successful vaccination programs. Unfortunately, vaccine uptake has been hindered by deferent factors and challenges. The objective of this study is to assess COVID-19 vaccine uptake and associated factors among the general population.

Beata thalassemia

Beta thalassemia syndrome by reduction or absence of B-globin chain synthesis. Without iron chelation therapy (ICT) the regular blood transfusion would increase the iron stores to several times. Endocrine glands are vulnerable to iron overload causing endocrine dysfunction.  Iron deposition within the parathyroid gland causes hypoparathyroidism particularly after ten years of age. Pancreatic islets are very susceptible to oxidative damage due to iron overload; their high divalent metal expression makes them highly susceptible to iron-catalyzing oxidative stress. The pathogenicity of osteopathy in  is multifactorial comprising environmental (diet and lifestyle), iatrogenic (medicines), genetic and acqui

Abstract

The current research aims to identify the attitudes towards the Covid-19 vaccine and the Locus of Control (internal, external) among university students, to identify the significance of the difference in attitudes towards the Covid-19 vaccine, the significance of the difference in the Locus of Control (internal, external) according to the gender variable (male, female), and to identify the significance of the difference in students’ attitudes towards Covid-19 vaccine according to the Locus of Control (internal, external). To achieve the objective of the research, the researcher developed two scales, a scale of (20) items to identify the attitudes toward a covid-19 vaccine, and a scale of the locus of c

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

This study aims to analyze the messages of a number of global news outlets on Twitter. In order to clarify the news outlets tactics of reporting, the subjects and focus during the crisis related to the spread of the Covid-19 virus. The study sample was chosen in a deliberate manner to provide descriptive results. Three news sites were selected: two of the most followed, professional and famous international news sites: New York Times and the Guardian, and one Arab news site: Al-Arabiya channel.

A total of 18,085 tweets were analyzed for the three accounts during the period from (1/3/2020) to (8/4/2020). A content analysis form was used to analyze the content of the news coverage.   The results indicate an increase in th

      Immunological genes, including TLR3 and RIG-I, have recently been established to have linked to predisposition to coronavirus disease 2019 (COVID-19) and its severity. The purpose of this case-control study (100 recovered COVID 19 cases and 100 healthy individuals) was to determine the role of gender, age, TLR3 and RIG-I genes in COVID-19 aggressiveness. TLR3 and RIG-I gene expression was detected using a quantitative real-time polymerase chain reaction (qRT-PCR). COVID-19 infection intensity increased with age and no statistical difference between males and females (p>0.05) was found. TLR3 and RIG-I gene expression levels were higher in patients compared to hea

Background: The post-operative acute abdominal complication is one of the most difficult clinical problems facing the surgeon, and it represents a unique challenge for him not only because of the difficulty in making a precise diagnosis but also in the decision for further management . Objective: discuss the post-operative acute abdominal complications requiring re-interventionType of the study: Cross sectional study. Methods : Patients with early post-operative Acute Abdominal complications ( within 30 days from the initial operation ) who required re-intervention were studied prospectively Results :The study included 82 patients 47 of them were females, their age ranging 7-87,Different types of the initial operation were reported,51 %