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

BACKGROUND: COVID-19 is resulted from severe acute respiratory syndrome coronavirus 2, which initiated in China in December 2019. Parasites are efficient immune modulators because their ability to stimulate an immune response in infected persons. AIM: This study aims to detect if there is a probable relationship between intestinal parasitic infections and COVID-19. METHODS: Ninety patients consulted at Al-Kindy Teaching Hospital (Al-Shifa center) from October 2020 till April 2021, confirmed infection with COVID-19 by PCR. Stool examination was done for detecting intestinal parasites. RESULTS: From 90 patients, males were 63 (70%), with median age 32 years, while females were 27 (30%), with age 24–44 years. Asymptomatic pati

Background: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected

The rapid spread of novel coronavirus disease
(COVID19) throughout the world without available
specific treatment or vaccine necessitates alternative
options to contain the disease. Historically, children
and pregnant women were considered high-risk
population of infectious diseases but rarely have been
spotlighted nowadays in the regular COVID-19
updates, may be due to low global rates of incidence,
morbidity, and mortality. However, complications did
occur in these subjects affected by COVID-19. We
aimed to explore the latest updates of
immunotherapeutic perspectives of COVID-19
patients in general population and some added details
regarding pediatric and obstetrical practice.
Immune system boo

The rapid spread of novel coronavirus disease(COVID19) throughout the world without availablespecific treatment or vaccine necessitates alternativeoptions to contain the disease. Historically, childrenand pregnant women were considered high-riskpopulation of infectious diseases but rarely have beenspotlighted nowadays in the regular COVID-19updates, may be due to low global rates of incidence,morbidity, and mortality. However, complications didoccur in these subjects affected by COVID-19. Weaimed to explore the latest updates ofimmunotherapeutic perspectives of COVID-19patients in general population and some added detailsregarding pediatric and obstetrical practice.Immune system boosting strategy is one of therecently emerging issue

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.

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