With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

ABSTRACT

Background: Al-Najaf province , Iraq , has experienced an outbreak of coronavirus disease 2019 (Covid-19). Epidemiological and clinical characteristics of (Covid-19) infection have been reported but a detailed clinical course and risk factors for mortality including medical comorbidities and severity of illness at time of presentation , have not been well described.

Methods: From February 24 to April 7, 2020, a case series study done on 123 PCR-confirmed cases of (Covid-19) admitted to Al-Hakeem Hospital And Quarantine Center (AHQC), in Al-Najaf Province, Iraq. Demographics, clinical and laboratory data  gathered from a local database at (AHQC). SPSS(statist

Background: The number of coronavirus infection cases has increased rapidly since early reports in the December 2019 in China. But data on the clinical features of infected peoples is variable from one country to the other.

Objective: Studying clinical features of patients with a positive RT PCR COVID – 19, in a group of Iraqi patients.

Results: The study included 200 patients with 133 (66.5%) males and 67 (33.5%) females, and age range of 14- 89 years, with mean age 46.4 years. A history of contact with a COVID -19 positive case was found in 80 patients (40%), Ischemic Heart Disease in 11 patients (5.5%), hypertension 34 (17%), diabetes mellitus 36 patients (18%). The

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

   The emerge of capitalism beside appearing modern and contemporary political systems which had become hold out it is semi-domination on more vital space of human community life, it is through some vital apparatus, which the free market apparatus had make important one which depend on achieve the privileges of the capitalism elite whom standing on it, especially the finance elite. Thus the achievement of the profit had become the main podcasted of those elite which whom the really advancer of the Globalization system, this is which incarnated by the appears and extend of the (COVID-19) fatality pandemic in the end of last year, whereas reveals widespread of it in more than one states in the world, especially the developed coun

Background: The most widely used vaccination against SARS-associated coronavirus (SARS-CoV-2) is the Pfizer vaccine, which provides protection against this virus. However, its ability to safeguard the oral cavity is unclear, and neither are the exact immunological biomarker levels it activates.

Aim of the study: To investigate the possibility that Pfizer vaccination protects the oral cavity against Covid-19.

Patients and Methods: The study group consisted of a total of 70 subjects (30 as the control group They were followed up before being vaccinated as non-vaccinated (maybe previously infected or non-infected or recovered) and 40 participants followed up three weeks after

News headlines are key elements in spreading news. They are unique texts written in a special language which enables readers understand the overall nature and importance of the topic. However, this special language causes difficulty for readers in understanding the headline. To illuminate this difficulty, it is argued that a pragmatic analysis from a speech act theory perspective is a plausible tool for a headline analysis. The main objective of the study is to pragmatically analyze the most frequently employed types of speech acts in the news headlines covering COVID-19 in Aljazeera English website. To this end, Bach and Harnish's (1979) Taxonomy of Speech Acts has been adopted to analyze the data. Thirty headlines have been collected f

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

Background: Severe forms of Coronavirus disease 2019 (COVID‐19) were found among 6 - 10% of all COVID-19 patients. Acute respiratory distress syndrome ARDS is non-cardiogenic pulmonary edema manifested by the rapid development of shortness of breath, tachypnea, and hypoxemia. Patients’ outcomes after critical care for COVID-19 have not been adequately documented in this low-resource environment, despite advocacy for prevention and response measures in low- and middle-income countries.

Objectives: To highlight the rate of severe illness among COVID-19 patients and its associated factors in Al-Imam Ali Hospital, Baghdad-Iraq 2021.

Patients and Methods: A descriptive cross