Background: Medical educators’ dissatisfaction may cause them to leave the practice of teaching, where it is often hard to replace those who have left. In addition, medical teaching staff dissatisfaction may indicate adverse quality for institution/ university organizations.

Objectives: To assess teaching staff satisfaction with online learning during the COVID pandemic at Al-Nahrain University /College of Medicine, Baghdad/Iraq.

Methodology: A cross-sectional study included a convenient sample of 50% of the teaching staff participating in the online academic year 2020-2021. The faculty satisfaction questionnaire was taken from the "Bolliger and Halupa" study, based on th

Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien

The research aims to explain the role of the flexible budget in assessing the feedback resulting from deviations by comparing the actual results with the planned performance in light of the economic crisis that the world witnessed during the spread of Corona disease. As most companies, including the Electronic Industries Company, face the problem of controlling production costs and are trying hard to reduce these costs to the lowest level starting from measuring these costs and allocating them and distributing them to products. This helps in controlling deviations and thus the flexible budget becomes a tool that helps in controlling elements Costs

The Coronavirus disease 2019 (COVID-19) pandemic is caused by the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was first identified in December 2019 in Wuhan, China. The outbreak was declared as a Public Health Emergency of International Concern in January 2020 and a pandemic in March 2020. In this study, a complete statistical analysis for SARS-CoV-2 pandemic in entire Iraq, as well as for each governorate separately, is performed for the first time. The study covers a period that starts from the beginning of the pandemic, in the 24^th of February 2020, until the 16^th of July 2020. It was clear that, although the average number of the reported infection cases was low during Feb

There is limited data and evidence about the effects of COVID-19 on Maternal health, especially when new information is emerging daily, through pregnancy, child birth and post natal period, women are vulnerable to have the infection, this article, aimed to show the suitable measures that should be applied for women at reproductive age who are suspected /confirmed with COVID -19 infection,

During pregnancy it is advisable to continue the antenatal care schedule, although reducing face to face visit is recommended (unless the pregnant condition required that ),and prioritize ANC at health facilities for high-risk pregnancy and during second half of pregnancy with adequate infection prevention control  measures.

Regardi

Factor analysis is distinguished by its ability to shorten and arrange many variables in a small number of linear components. In this research, we will study the essential variables that affect the Coronavirus disease 2019 (COVID-19), which is supposed to contribute to the diagnosis of each patient group based on linear measurements of the disease and determine the method of treatment with application data for (600) patients registered in General AL-KARAMA Hospital in Baghdad from 1/4/2020 to 15/7/2020. The explanation of the variances from the total variance of each factor separately was obtained with six elements, which together explained 69.266% of the measure's variability. The most important variable are cough, idleness, fever, headach

    COVID-19 is an infectious pandemic disease which is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Up to date, scientists are trying to identify a new specific antiviral drug to overcome this disease. Different methods are under study and evaluation in the entire world to control the virus, including blood plasma, blood purification, and antimicrobial and antiviral agents; however, there are no approved drugs yet. This review is focused on the conducted clinical trials worldwide, including the Iraq- Kurdistan region, China, USA, and Europe, to fi

     The worldwide pandemic Coronavirus (Covid-19) is a new viral disease that spreads mostly through nasal discharge and saliva from the lips while coughing or sneezing. This highly infectious disease spreads quickly and can overwhelm healthcare systems if not controlled. However, the employment of machine learning algorithms to monitor analytical data has a substantial influence on the speed of decision-making in some government entities.        ML algorithms trained on labeled patients’ symptoms cannot discriminate between diverse types of diseases such as COVID-19. Cough, fever, headache, sore throat, and shortness of breath were common symptoms of many bacterial and viral diseases.

This research focused on the nu

     This paper focuses on choosing a spatial mixture model with implicitly includes the time to represent the relative risks of COVID-19 pandemic using an appropriate model selection criterion. For this purpose, a more recent criterion so-called the widely Akaike information criterion (WAIC) is used which we believe that its use so limitedly in the context of relative risk modelling. In addition, a graphical method is adopted that is based on a spatial-temporal predictive posterior distribution to select the best model yielding the best predictive accuracy. By applying this model selection criterion, we seek to identify the levels of relative risk, which implicitly represents the determination of the number of the model components o