A case-control study was performed to examine age, gender, and ABO blood groups in 1014 Iraqi hospitalized cases with Coronavirus disease 2019 (COVID-19) and 901 blood donors (control group). The infection was molecularly diagnosed by detecting coronavirus RNA in nasal swabs of patients.

Coronavirus diseases 2021 (COVID-19) on going situation in Iraq is characterized in this paper. The pandemic handling by the government and the difficulties of public health measures enforcement in Iraq. Estimation of the COVID-19 data set was performed. Iraq is endangered to the pandemic, like the rest of the world besides sharing borders with hotspot neighbouring country Iran. The government of Iraq launched proactive measures in an attempt to prevent the viral spread. Nevertheless, reports of new cases keep escalating leaving the public health officials racing to take more firm constriction to face the pandemic. The paper bring forth the current COVID-19 scenario in Iraq, the government measures towards the public health challenges, and

  The Covid-19 virus disease has been shown to affect numerous organs and systems including the liver. The study aimed to compare lipid profiles and liver enzyme levels in individuals who had recovered from Covid-19 infection. To achieve the study objectives, liver Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT), Alkaline phosphatase (ALP),  Random Blood Sugar (RBS) and Lipid profile which include cholesterol, High-Density Lipoprotein (HDL), Triglycerides (T.G), Low-Density Lipoprotein (LDL), and Very low-density Lipoprotein (VLDL) were determined.

One hundred twenty serum samples were obtained, of which fifty samples were utilized as the control healthy persons (not affected by COVID) and seventy samples came f

During infection, T. gondii disseminates by the circulatory system and establishes chronic infection in several organs. Almost third of humans, immunosuppressed individuals such as HIV/AIDS patients, cancer patients, and organ transplant recipients are exposed to toxoplasmosis. Therefore, the study aimed to investigate the possibility that Toxoplasma infection could be a risk factor for COVID-19 patients and its possible correlation with C-reactive protein and ferritin. Overall 220 patients referred to the Al Furat General Hospital, Baghdad, Iraq were enrolled from 2020–2021. All serum samples were tested for T. gondii immunoglobulins (IgG and IgM) antibodies, C-reactive protein and ferritin levels. In patients with COVID-19, the results

Background: In December 2019, an episode of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV2) was reported in Wuhan, China and has spread around the world, increasing the number of contagions. Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are common herpesviruses that can cause persistent latent infections and affect the developing immune system.The study was conducted to explore the prevalence and reactivation of CMV and EBV antibodies in COVID-19 patients group in comparison to healthy group and to investigate the association between the presence of these viruses with each of severity of disease and oral hygiene. Materials and Methods: Eighty Five subjects were participated in this case control study (5

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

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the