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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 study. The most encountered orthodontic problem was broken or movable bracket (55.6%), followed by long pocking wire 35.2%. In addition, 55.6% of the participants preferred to wait for the next appointment to see their orthodontist, and only 5.6% tried to treat the problem personally. There was no significant relationship between pain level, gender and age, whereas a strong significant association was found between pain intensity and orthodontic problems or emergencies. COVID-19 had a negative impact on orthodontic follow-up visits. The intensity of pain was strongly correlated with orthodontic problems or emergencies. Therefore, more attention should be given to patients, focusing on teaching them how to manage orthodontic emergencies during situations such as an outbreak.

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Publication Date
Tue Mar 25 2025
Journal Name
Italian Journal Of Medicine
Cytokine profile in COVID-19 infection: focus on interleukin-13, interleukin-33, and tumor necrosis factor-α as immunological markers
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COVID-19 is a pandemic disease that has a wide spectrum of symptoms from asymptomatic to severe fatal cases due to hyperactivation of the immune system and secretion of pro-inflammatory cytokines. This study aimed to assess the level and impact of interleukin (IL)-13, IL-33, and tumor necrosis factor (TNF)-α cytokines on immune responses in mild and moderate COVID-19-infected Iraqi patients. A prospective case-control study was conducted from January 2023 to January 2024; it included 80 patients infected with moderate COVID-19 infection who consulted in different private clinics and 40 healthy controls. The serum of both groups was tested for quantification of serum IL-13, IL-33, and TNF-α using the human enzyme-linked immunosorbe

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Tue Dec 30 2008
Journal Name
Al-kindy College Medical Journal
Three Years Experience in the Management of Uterine Rupture at Al-Battool Teaching Hospital Mosul-Iraq
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Background: Ruptured uterus is a catastrophic event to both
mother and her fetus. Apart from maternal and fetal mortality
rates, the incidence of rupture of uterus is often taken as an
index of the standard of obstetric care.
Objective: To determine the frequency, causes, management
outcome of ruptured uterus at Al Batool maternity hospital.
Method: The study was conducted in the department of
obstetrics and gynecology at Al Batool maternity hospital
Mosul-Iraq over a period of three years from October 1st 2002
to August 30th 2005. All the cases of uterine rupture presented
during the study period were recorded and managed in the
department. Data was recorded on designed forms.
Results: Thirty nine cas

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Publication Date
Tue May 26 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of ER: YAG laser on enamel resistance to caries during orthodontic treatment: An in vitro study
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Background: One common undesirable side effect of orthodontic treatment with fixed appliances is the development of incipient caries lesions around brackets, particularly in patients with poor oral hygiene. Different methods have been used to prevent demineralization; the recent effort to improve the resistance against the demineralization is by the application of lasers. Materials and method: Thirty human premolars extracted for orthodontic purposes were used to test the effect of two energy level of ER-YAG laser on enamel resistance to demineralization. The brackets were bonded on the teeth and all the labial surface excluding 2 mm area gingival to the brackets were painted with acid resistance varnish. Three groups were generated. The fi

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Publication Date
Tue May 26 2026
Journal Name
University Of Anbar Sport And Physical Education Science Journal
The study of comparing the cognitive teaching method effect ( total and analytic ) in teaching the counter- attack of Epee
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The research's aim is to place two teaching methods ( total and analytical method) and to know which one of them is better than the other in teaching the counter-attack with Epee. The researchers have used the experimental method for being considered suitable to solve the problem of the research. The sample of the research includes third –stage female students of college of physical education and sport sciences / Baghdad University in the subject of fencing, their number amounted 60 female students. It has been used SPSS for processing the results. They have concluded that the two groups of the research and the two methods (( total and analytical) have learnt the counter- attack of the two over mentioned groups. they have recommended to c

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Publication Date
Wed Jan 01 2020
Journal Name
Studies In Big Data
COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor
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Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

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Publication Date
Mon Mar 15 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of an Educational Program on Nursing Staffs' Knowledge about Uses of Steroids and Their Side Effects in Al-Diwaniya Teaching hospital
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Objective: To determine the effectiveness of the educational program on nursing staffs' knowledge about uses of steroids and their side effects.
Methodology: A pre-experimental study design (one group design: pre-test and post-test) was used. This study was conducted in Al-Diwaniya Teaching Hospital for the period from ( 28th May to 10 th June, 2020) on a non-probability (purposive) sample consisting of (30 nurses) working in Oncology unit. A questionnaire was built as a data collection tool and consisted of two parts:
First part: The demographic characteristics of the nursing staff (gender, age, level of education, years of experience in hospital, participation in training courses related to nursing care for a patients undergoing

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Publication Date
Tue Feb 01 2022
Journal Name
Archives Of Razi Institute
Imipenem Resistance in Gram-Negative Bacteria in the Central Pediatric Teaching Hospital in Baghdad, Iraq
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Antimicrobial resistance (AMR) is a serious challenge for infectious disease prevention and treatment, according to the World Health Organization. It is a worldwide problem caused primarily by inappropriate and insufficient therapy, misuse of antimicrobials without physician supervision, unnecessary hospital readmissions, and other factors. AMR has several consequences, including increased medical costs and mortality. The present study aimed to evaluate imipenem resistance in gram-negative bacteria in Central Pediatric Teaching Hospital in Baghdad, Iraq, and determine this bacteria resistance in different samples. Initially, a total of 100 different samples were collected from child patients from October 1, 2020, to August 31, 2021. Each is

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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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