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 issues allowing the body defensemechanism to produce virus-neutralizing antibodies tocounteract the viral impacts on multiple organdamage. Measles vaccination (which is universallyused for children in many countries, butcontraindicated during pregnancy) could urge thebody to produce these antibodies which may applytheir effects through cross-reactivity of measlesvaccine and COVID-19 antigenic proteins. Inaddition, intravenous immunoglobulin andconvalescent plasma could have such neutralizingantibody effect leading to clinical improvement andviral elimination. Pediatric and obstetrical experiencehas appeared in previous publications.Human monoclonal antibodies are the futurepromising approach to treat and prevent COVID-19with the use of tocilizumab in recent studies. Pediatricdata are still in progress while no pregnancy ongoingtrials are planned up to date.The better understanding of the host antiviral responsemay pave the way to develop immunotherapeuticplans against COVID-19 in the near upcoming days.
<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreObjective: Pregnancy-induced hypertension (PIH) is a major pregnancy complication that leads to maternal mortality. Here, we have scrutinized the correlation between serum levels of hydrogen peroxide (H2O2) and superoxide dismutase (SOD) in PIH.Methods: Serum samples were collected from 80 Iraqi women (40 women with PIH as patients group, 20 normotensive pregnant women as a positive control, and 20 normotensive non-pregnant women as a negative control) all groups were diagnosed clinically.Results: Serum of H2O2 and SOD levels was measured for all studied groups. Results showed that there were no significant variances in age and gestational age distribution between all studied groups. Furthermore, result showed that the serum level o
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The prevalence of gastrointestinal symptoms of COVID-19 is variable with different types of presentations. Some of them many present with manifestations mimicking surgical emergencies. Yet, the pathophysiology of acute abdomen in the context of COVID-19 remains unclear. We present a case of a previously healthy child who presented with acute appendicitis with multisystemic inflammatory syndrome. We also highlight the necessity of considering the gastrointestinal symptoms of COVID-19 infection in pediatric patients in order to avoid misdiagnosis and further complications. |
Persuasion is an indispensable skill in everyday life; that is why, it has aroused researchers’ interest. This study aims to investigate the most frequently used persuasive strategies in texting WHO COVID-19 Virtual Press Conferences and explore how these strategies are employed to achieve persuasive messages.To this end, a text of WHO COVID-19 Virtual Press Conferences has been chosen randomly to be analyzed based on Dillard and Shen’s (2013) “Persuasive strategies in Health Campaigns”. A qualitative method has been adopted in analyzing the selected data to investigate the credibility and validity of the persuasive strategies used in such a domain. Findings have shown that most of the persuasive appeals based on the adopted mode
... Show More<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
... Show MoreIn 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
... Show MoreThis research study Blur groups (Fuzzy Sets) which is the perception of the most modern in the application in various practical and theoretical areas and in various fields of life, was addressed to the fuzzy random variable whose value is not real, but the numbers Millbh because it expresses the mysterious phenomena or uncertain with measurements are not assertive. Fuzzy data were presented for binocular test and analysis of variance method of random Fuzzy variables , where this method depends on a number of assumptions, which is a problem that prevents the use of this method in the case of non-realized.
Background: Childhood meningitis is a major
cause of morbidity and mortality, Hemophilus
influenza b (Hib) is the most common cause in
many countries, especially below 5 years and
before the development of conjugated Hib vaccine,
it is followed by Streptococcus Pneumonia, and
then N. meningitides, in addition to other
microorganisms.
Objective: To identify the causative organisms
of bacterial meningitis and to identify the factors
predisposing significantly to the incidence of
bacterial meningitis.
Method: This cross sectional , study was done in
Al-Elwia Pediatric Hospital during the period 1st
of January 2007 to 30th of June 2007.Eighty four
patients with presumptive diagnosis of meningitis<