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CT scan and deep learning for COVID-19 detection
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Publication Date
Wed Mar 01 2023
Journal Name
Ecti Transactions On Computer And Information Technology
Diagnosis of COVID-19 Infection via Association Rules of Cough Encoding
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Article information: COVID-19 has roused the scientic community, prompting calls for immediate solutions to avoid the infection or at least reduce the virus's spread. Despite the availability of several licensed vaccinations to boost human immunity against the disease, various mutated strains of the virus continue to emerge, posing a danger to the vaccine's ecacy against new mutations. As a result, the importance of the early detection of COVID-19 infection becomes evident. Cough is a prevalent symptom in all COVID-19 mutations. Unfortunately, coughing can be a symptom of various of diseases, including pneumonia and inuenza. Thus, identifying the coughing behavior might help clinicians diagnose the COVID-19 infection earlier and distinguish

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Publication Date
Wed Apr 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving Nonlinear COVID-19 Mathematical Model Using a Reliable Numerical Method
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This research aims to numerically solve a nonlinear initial value problem presented as a system of ordinary differential equations. Our focus is on epidemiological systems in particular. The accurate numerical method that is the Runge-Kutta method of order four has been used to solve this problem that is represented in the epidemic model. The COVID-19 mathematical epidemic model in Iraq from 2020 to the next years is the application under study. Finally, the results obtained for the COVID-19 model have been discussed tabular and graphically. The spread of the COVID-19 pandemic can be observed via the behavior of the different stages of the model that approximates the behavior of actual the COVID-19 epidemic in Iraq. In our study, the COV

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Biochemical Action of Vaccines in Iraqi Patients with COVID-19 Infection
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      The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc :  COVID-19 patients ( without vaccine ) , Gp1: COVID-19 patients took one dose of Pfizer Biontech, Gp2 : COVID-19 patients took two doses of Pfizer Biontech, Ga1 : patients took one dose of AstraZeneca Oxford vaccine , Ga2: patients took two doses of AstraZeneca Oxford vaccine , Gs1 : patients took one dose of Sinopharm vaccine and Gs2:

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Intelligent Systems
An online COVID-19 self-assessment framework supported by IoMT technology
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Abstract<p>As COVID-19 pandemic continued to propagate, millions of lives are currently at risk especially elderly, people with chronic conditions and pregnant women. Iraq is one of the countries affected by the COVID-19 pandemic. Currently, in Iraq, there is a need for a self-assessment tool to be available in hand for people with COVID-19 concerns. Such a tool would guide people, after an automated assessment, to the right decision such as seeking medical advice, self-isolate, or testing for COVID-19. This study proposes an online COVID-19 self-assessment tool supported by the internet of medical things (IoMT) technology as a means to fight this pandemic and mitigate the burden on our nation</p> ... Show More
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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Cluster Analysis of Biochemical Markers as Predictor of COVID-19 Severity
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Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien

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Publication Date
Tue Jul 26 2022
Journal Name
International Journal Of Pharmacy Practice
What might COVID-19 patients experience after recovery? A comprehensive review
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Abstract<sec> <title>Objectives

The objective of this review was to describe the COVID-19 complications after recovery.

Methods

The researchers systematically reviewed studies that reported post-COVID-19 complications from three databases: PubMed, Google Scholar and the World Health Organization (WHO) COVID-19 database. The search was conducted between 21 November 2020 and 14 January 2021. Inclusion criteria were articles written in English, with primary data, reporting complications of COVID-19 after full

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
Statistical Analysis of COVID-19 Pandemic Across the Provinces of Iraq
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The Coronavirus disease 2019 (COVID-19) pandemic is caused by the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was first identified in December 2019 in Wuhan, China. The outbreak was declared as a Public Health Emergency of International Concern in January 2020 and a pandemic in March 2020. In this study, a complete statistical analysis for SARS-CoV-2 pandemic in entire Iraq, as well as for each governorate separately, is performed for the first time. The study covers a period that starts from the beginning of the pandemic, in the 24th of February 2020, until the 16th of July 2020. It was clear that, although the average number of the reported infection cases was low during Feb

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Publication Date
Thu Jul 22 2021
Journal Name
Open Access Macedonian Journal Of Medical Sciences
Intestinal Parasitic Infections in Relation to COVID-19 in Baghdad City
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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

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Publication Date
Thu Dec 30 2021
Journal Name
Al-kindy College Medical Journal
Clinical Analysis of Four Maternity Deaths in Iraq by COVID-19
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This study aims to identify maternal death cases caused by Coronavirus infection 2019 pneumonia, including disease progression, fetal consequences, and the fatality cause.

Patients and methodology: A retrospective case collection of Iraqi pregnant women in their second and third trimesters diagnosed with COVID-19 pneumonia and died due to it.

The four cases were all of a young age, had a brief complaint period, and had no comorbidities. Fever, dyspnea, and fatigue were the most common symptoms. Hypoxia was present in all cases and was the cause of mortality in three cases, with thromboembolism being a potential cause in the fourth. Prelabour membrane breakup, fetal growth restriction, and fetal death are al

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning
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     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

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