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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 convolutional neural network that uses other activation functions (exponential linear unit (ELU), rectified linear unit (ReLU), Swish, Leaky ReLU, Sigmoid), and the result is that utilizing CWNN gave better results for all performance metrics (accuracy, sensitivity, specificity, precision, and F1-score). The results obtained show that the prediction accuracies of CWNN were 99.97%, 99.9%, 99.97%, and 99.04% when using wavelet filters (rational function with quadratic poles (RASP1), (RASP2), and polynomials windowed (POLYWOG1), superposed logistic function (SLOG1)) as activation function, respectively. Using this algorithm can reduce the time required for the radiologist to detect whether a patient has COVID or not with very high accuracy.</p>

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Publication Date
Sun Jun 27 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Depression among Nurses Providing Care for Patients with COVID-19 at Baqubah Teaching Hospital
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Objectives: The present study aims at detecting the depression among nurses who provide care for infected patients with corona virus phenomenon and to find out relationships between the depression and their demographic characteristics of age, gender, marital status, type of family, education, and years of experience of nurses in heath institutions, infection by corona virus, and their participation in training courses.
Methodology: A descriptive study is established for a period from October 10th, 2020 to April 15th, 2021. The study is conducted on a purposive (non-probability) sample of (100) nurse who are providing care for patients with COVID-19 and they are selected from the isolation wards. The instrument of the study is develope

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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
Tue Apr 13 2021
Journal Name
Latin American Journal Of Pharmacy
The Experience with Hospitalized COVID-19 Patients in Al-Basra, Iraq: Predictors of the disease severity
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SUMMARY. The objectives of the present study were to assess the possible predictors of COVID-19 severity and duration of hospitalization and to identify the possible correlation between patient parameters, disease severity and duration of hospitalization. The study included retrospective medical record extraction of previous coron avirus COVID-19 patients in Basra hospitals, Iraq from March 1st and May 31st, 2020. The information of the participants was investigated anonymously. All the patients’ characteristics, treatments, vital signs and laboratory tests (hematological, renal and liver function tests) were collected. The analysis was conducted using the SPSS (version 22, USA). Spearman correlation was used to measure the relations

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Publication Date
Mon Jun 26 2023
Journal Name
International Conference On Scientific Research &amp; Innovation (icsri 2022)
Age and gender profile of coronavirus disease 2019 (COVID 19) in Quarantine Center in Baghdad, Iraq
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Publication Date
Sat Jan 01 2022
Journal Name
Annals Of Parasitology
Serum levels of C-reactive protein and ferritin in COVID-19 patients infected with Toxoplasma gondii
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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

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Medicine And Life
The effect of COVID-19 on emergencies and pain among orthodontic patients attending a teaching hospital
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This study aimed to evaluate the effect of the COVID-19 outbreak on emergencies and pain among orthodontic patients attending a teaching hospital. The study was conducted among orthodontic patients receiving active orthodontic treatment or in a retention period at the College of Dentistry, University of Baghdad, Iraq. Their participation was voluntary, and they filled out an Arabic-translated questionnaire. The survey included general information, orthodontic problems, and a numerical rating scale for pain assessment. We used descriptive and inferential statistics (frequencies and intersecting frequencies), chi-square test and linear regression. Out of 75 orthodontic patients, only 54 (15 males and 39 females) were included in the s

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Studying the Effect of COVID-19 on Liver Enzymes and Lipid Profile in Iraqi Recovering Patients
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  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

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Publication Date
Wed Sep 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Prevalence of viral co-infection among COVID-19 cases in association disease severity and oral hygiene
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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

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Estimate the Partial Linear Model Using Wavelet and Kernel Smoothers
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This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

 

 

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Digital Image Watermarking Using Arnold Scrambling and Berkeley Wavelet Transform
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Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

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