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Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.

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Publication Date
Wed Nov 08 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment, And Sustainability: Tmrees23fr
Studying the relationship between the number of unit cells and the dislocation density of a crystal through the x-ray diffraction pattern of barium oxide nanoparticles
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In this research, the X-ray diffraction pattern was used, which was obtained experimentally after preparation of barium oxide powder. A program was used to analyze the X-ray diffraction lines of barium oxide nanoparticles, and then the particle size was calculated by using the Williamson-Hall method, where it was found that the value of the particle size is 25.356 nm. Also, the dislocation density was calculated, which is equal to1.555 x1015 (lines/nm2), and the value of the unit cell number was also calculated, as it is equal to 23831.

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Publication Date
Thu Dec 01 2016
Journal Name
International Journal Of Scientific Research
Anatomical differences of Cerebellar vermismeasurement values in healthy adult men andwomen using MRI images
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Background: e cerebellum is divided into two hemispheres and contains a narrow midline zone called thevermis. A set of large folds are conventionally used to divide the overall structure into ten smaller "lobules". evermis receives fibres from the trunk and proximal portions of limbs, But the question is that does the cerebellum have the same measurementvalues in males and females of the same age?Material and method: e present study used 80 sectional brain MRI images (40: males, 40: females); 35-50 years old as indices of size for thevermian structures of the Cerebellum. is middle age group was taken because as known generally it could be neither an age of growth as inthe young nor of atrophy as in old individuals. e aim rega

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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
Tue Jun 30 2020
Journal Name
Dialogo
The Problems of Applying Psychological, Educational and Political Measurement Instruments in light of the Prevalence of the Corona virus (Covid-19)
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Publication Date
Tue Feb 28 2023
Journal Name
Tropical Journal Of Natural Product Research
Genetic Association of Angiotensin-converting enzyme 2 ACE-2 (rs2285666) Polymorphism with the Susceptibility of COVID-19 Disease in Iraqi Patients
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Significant risks to human health are posed by the 2019 coronavirus illness (COVID-19). SARS coronavirus type 2 receptor, also known as the major enzyme in the renin-angiotensin system (RAS), angiotensin-converting enzyme 2 (ACE-2), connects COVID-19 and RAS. This study was conducted with the intention of determining whether or not RAS gene polymorphisms and ACE-2 (G8790A) play a part in the process of predicting susceptibility to infection with COVID-19. In this study 127 participants, 67 of whom were deemed by a physician to be in a severe state of illness, and 60 of whom were categorized as "healthy controls" .The genetic study included an extraction of genomic DNA from blood samples of each covid 19 patients and healthy control

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Publication Date
Tue Oct 04 2022
Journal Name
Cureus
The Impact of Angiotensin Converting Enzyme-2 (ACE-2) on Bone Remodeling Marker Osteoprotegerin (OPG) in Post-COVID-19 Iraqi Patients
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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Design & Nature And Ecodynamics
Artificial Neural Network Assessment of Groundwater Quality for Agricultural Use in Babylon City: An Evaluation of Salinity and Ionic Composition
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Publication Date
Wed Jul 10 2024
Journal Name
The Open Neuroimaging Journal
The Efficacy of Bedside Chest Ultrasound in the Detection of Traumatic Pneumothorax
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Background

Chest X-rays have long been used to diagnose pneumothorax. In trauma patients, chest ultrasonography combined with chest CT may be a safer, faster, and more accurate approach. This could lead to better and quicker management of traumatic pneumothorax, as well as enhanced patient safety and clinical results.

Aim

The purpose of this study was to assess the efficacy and utility of bedside US chest in identifying traumatic pneumothorax and also its capacity to estimate the extent of the lesion in comparison to the gold standard modality chest computed tomography.

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Publication Date
Wed Apr 01 2015
Journal Name
Al–bahith Al–a'alami
Pictures of neighboring countries to the Iraqi public
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the mental image is so important in human life as one of the major standers for his trends and behavior, and as the human nature requires to interest in things based on how much it’s close to and how much it effects on his interest, So the neighborhood countries was one  of the topics that occupied the attention of the Iraqi individual and pushed him to form perceptions of them based on the cultural heritage and the historical relations of Iraq with these countries as well as the actions of neighboring countries on Iraq and the resulting effects on the course of events. the mental image is so important in human life as one of the major standers for his trends and behavior, and as the human nature requires to interest in things bas

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Deep Learning of Diabetic Retinopathy Classification in Fundus Images
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Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

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