The coronavirus is a family of viruses that cause different dangerous diseases that lead to death. Two types of this virus have been previously found: SARS-CoV, which causes a severe respiratory syndrome, and MERS-CoV, which causes a respiratory syndrome in the Middle East. The latest coronavirus, originated in the Chinese city of Wuhan, is known as the COVID-19 pandemic. It is a new kind of coronavirus that can harm people and was first discovered in Dec. 2019. According to the statistics of the World Health Organization (WHO), the number of people infected with this serious disease has reached more than seven million people from all over the world. In Iraq, the number of people infected has reached more than tw

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.

      Coronavirus 2 is the cause of coronavirus disease 2019 (COVID-19), which leads to severe acute respiratory illness. Matrix metalloproteinases (MMPs) have been linked to leukocyte infiltration and chemokine activation during inflammatory responses. Tissue inhibitors of metalloproteinase (TIMP) family are thought to dampen the proinflammatory effects of these MMPs. The molecular pathways of lung fibrosis are mediated by MMPs and TIMPs. In this study, we sought to investigate the probable link between MMPs, specifically MMP-3, TIMP-2, and COVID-19. The study included 58 COVID-19 patients and 30 apparently healthy individuals matched in terms of age and sex. Multiplex real- time PCR was used to detect the ORF1ab, E, and N genes of

Chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm arises from Bcr-Abl gene translocation(called Ph chromosome) in hematopoietic stem cells (HSCs).JAK2V617F mutation is an acquired singlenucleotide polymorphism (SNP) occurs in JAK2 gene and is associated with many hematological malignancyother than CML. This study aimed to investigate the prevalence of JAK2V617F mutation and serum levels ofalkaline phophatase (ALP) and lactate dehydrogenase (LDH) in Ph+ CML Iraqi patients treated with imatinib.Blood samples were collected from 42 Ph+ CML patients who have been received at least six month therapywith imatinib. DNA was extracted, and real time polymerase chain reaction (qPCR) was used for JAK2V617Fdetection. Serum levels of A

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Background: Acute appendicitis is a common surgical
problem that is associated with an acute-phase reaction.
Previous studies have shown that cytokines and acutephase proteins are activated and may serve as indicators for
appendicitis.
Objective: The aim of this study was to evaluate of serum
levels of interleukin-6 (IL-6) in correlation to the severity
to acute appendicitis.
Methods: This is a prospective study from December 2008
to March 2009 of patients who had appendectomy in
Department of Surgery, Al-Kindy Teaching Hospital -
Baghdad/Iraq. Serum for estimating levels of interleukin-6
(IL-6) was taken pre-operatively. Depending on the
macroscopic evidence during the operation and the
histopathol

Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.

In the present study, an attempt has been made to study the change in water quality of the river in terms of turbidity during lockdown associated with COVID-19. Iraq announced the longest-ever lockdown on 25 March 2020 due to COVID-19 pandemic. 

In the absence of ground observations, remote sensing data was adopted, especially during this period. The change in the visible region's spectral reflectance of water in part of the river has been analyzed using the Landsat 8 OLI multispectral remote sensing data at Tigris River, Salah al-Din province (Bayji / near the refinery), Iraq. It was found that the green and red bands are most sensitive and can be used to estimate turbidity. Furthermore, the temporal variation in turbidity was a