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CT scan and deep learning for COVID-19 detection
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Publication Date
Mon Jan 01 2024
Journal Name
Russian Electronic Journal Of Radiology
COHORT COMPARATIVE STUDY OF COVID-19 VACCINATED AND NON-VACCINATED PATIENTS DEPENDING ON CT CHEST FINDINGS BETWEEN IRAQI AND JORDANIAN POPULATION
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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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
Fri Jan 20 2023
Journal Name
Bionatura
Impact of inflammatory markers, dread diseases and cycle threshold (Ct) Values in COVID-19 progression. Revis Bionatura 2023; 8 (1) 33
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Publication Date
Fri Apr 29 2022
Journal Name
Sar Journal Of Surgery
Variation of Sphenoid Sinus Pneumatization on CT scan in A Sample of Iraqi Patients
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Background: Computerized tomography scan can show the detailed anatomy of the nose and paranasal sinuses. The sphenoid sinus is a very important corridor for the skull base because of its central position. This sinus has a great range of variation and can put structures around at risk during surgery. This study aims to examine the variation of the sphenoid sinus, and its relation to other structures around it, in this sample of Iraqi patients. Materials and Methods: CT scans of 122 patients, were obtained, and submitted for examination and measurements, during the period between September 2020 and September 2021. Observation of The sphenoid sinus pneumatization pattern, clival extension, Onodi cell, and lateral pneumatization of SS.

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Sat Mar 29 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of the relationship between maxillary sinus floor and maxillary posterior teeth root apices using spiral CT scan
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Background: The purpose of this study is to investigate the relationship between the roots of the maxillary posterior teeth and the maxillary sinus using spiral computed tomography, and measured the distances between the roots of the maxillary posterior teeth and the sinus floor. Materials and Methods: The sample of the present study was a total of 120 Iraqi subject (60 males & 60 females) aged (20-60) years old, who admitted to spiral Computed Tomography scan unit in AL-Zahraa hospital in AL-Kut city to have Computed Tomography scan of the brain and paranasal sinuses who had complaints of headaches or with suspicion of sinusitis but without pathological findings in maxillary sinuses. From November 2012 to April 2013, CT sagittal reconstruc

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