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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: patients took two doses of Sinopharm vaccine. Patients were compared with healthy subjects (without vaccine) as a control group (Gh). The D-dimer level was highly significantly increased in Gc compared with Gh and was highly significantly decreased in Gp1 , Ga1 , Ga2 , significantly decreased in Gp2 and non-significantly decreased in Gs1 and highly significant increased in Gs2 compared with Gc. CRP level was significantly increased in Gc compared with Gh while it was significantly decreased in Gp1, Gp2, Ga1 , Ga2 , Gs1 , Gs2 compared with Gc. IgG and IgM levels were increased in Gc but decreased after taking vaccines ( except Ga2 for IgG and Gp2 for IgM )   The present study submits a novelty to the field of COVID-19 by highlighting the chemical aspects of vaccines used in Iraq

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<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

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<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

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Publication Date
Tue Mar 01 2022
Journal Name
Process Safety And Environmental Protection
Safety and health management response to COVID-19 in the construction industry: A perspective of fieldworkers
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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<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

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Wed Mar 15 2023
Journal Name
Bionatura
Evaluation of serum Interleukin 36 in Iraqi patients with Rheumatoid arthritis
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Rheumatoid arthritis is a worldwide inflammatory chronic autoimmune disease with varying severity. Due to no definitive cure for this disease, current therapies aim to decrease the pain and slow further damage. The interleukin (IL)‐36 cytokine was little known for its role in rheumatoid arthritis; this research aimed to evaluate the serum IL36 levels in RA patients compared to healthy controls. This study included 80 patients with rheumatoid arthritis registered at the Rheumatology Clinic in Baghdad teaching hospital. The patients were divided into three groups based on the treatments received. Group 1 included patients treated with biological therapy (etanercept, adalimumab), Group2 patients with non-biological treatment (methotr

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
The Immunohistochemically Estimation of CD63 in Iraqi Patients with Gastric Cancer
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CD63 is -one of the tetraspanin family proteins, which are regarded as: hallmark exosomal markers because it is absent from other types of vesicles. It is expressed in the cell membrane of cancer cells, and cytoplasm of stromal cells. Objective: To assess CD63 expression in gastric cancer (GC) patients, and detected if it could be used as a predictive marker. Furthermore, the current study aimed to find the correlation between CD63 expression and clinicopathological parameters as: gender, age, invasion depth, histopathological type, involvement of lymph nodes, grade and stages of GC (TNM). The current study is a retrospective study in the period time from (2018 to-2020); 50 randomly patients formalin-fixed paraffin embedded blocks (FFPE)

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine &amp; Toxicology
Effectiveness of Deep Brain Stimulation in Iraqi Patients with Parkinson Disease
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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Global Pharma Technology
Influence of immune engines in iraqi patients with acute myeloid leukemia
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Acute myeloid leukemia (AML) is heterogeneous disorders originated from the abnormalities in the proliferation and maturation of myeloid progenitors in bone morrow. There is a clinical correlation between immunity engines and disease progression, but this relationship is not completely clear yet. This study was designed to assess the full immune response in Iraqi patients diagnosed with AML. Patients and healthy volunteers were divided into three groups: newly diagnosed untreated, under chemotherapy treatment patients and control group. A significant reduction were seen in C4 and IFN-γ levels in both untreated and treated groups with no significant difference between untreated and treated groups. On the other hand, IL-2 and IL-8 levels inc

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Publication Date
Tue Oct 31 2023
Journal Name
Onkologia I Radioterapia
The prevalence of HSV1 expression in Iraqi patients with colorectal cancer
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Background: Colorectal Cancer (CRC) is one of the most serious health problems and Herpes viridae may hasten the progression of colon cancer. Aim: The purpose of conducting this research is to investigate the existence of Herpes Simplex Virus (HSV1) infection in samples of Colorectal Cancer (CRC) compared with normal tissue. Material and Methods: 40 samples of tissues (30 patients ) with CRC, and (10 samples) of normal tissue (without cancer) were obtained, for immunohistochemically analysis of Herpes Simplex Virus (HSV1) expression Results: The results showed no significant data to justify the link between both Herpes Simplex Virus (HSV1) and human colorectal cancer. Despite of presence of Herpes Simplex Virus (HSV1) found in

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