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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
Tue Dec 25 2018
Journal Name
Journal Of Engineering Science And Technology
RIETVELD TEXTURE REFINEMENT ANALYSIS OF LINDE TYPE A ZEOLITE FROM X-RAY DIFFRACTION DATA
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Publication Date
Sun Jan 01 2023
Journal Name
Rawal Medical Journal
Procalcitonin Level In COVID-19 Patients: A single center study
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Objective: The study the association of procalcitonin (PCT) and c-reactive protein (CRP) levels in COVID-19 patients and it's role as a guide in progress and management of those patients. Methodology: This cross-sectional study analyzed 200 CIOVID-19 patients in a single privet center in Baghdad, Iraq from January 1, 2021 to January 1, 2022. Demographic data like age, sex, and clinical symptoms were recorded. High sensitivity CRP and PCT in the serum were measured via dry fluorescence immunoassay (Lansionbio-China). Results: Out of 200 patients, 50 had moderate Covid and 150 had severe disease. Mean serum PCT levels was 0.039±0.05 ng/mL in the moderate group (range 0.011-0.067) and 0.43±0.21 ng/mL in the severe group (range 0.21

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
MODELING DEATH RATE OF THE COVID-19 PANDEMIC IN IRAQ
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Publication Date
Sun Nov 01 2020
Journal Name
Travel Medicine And Infectious Disease
Incidence of the COVID-19 in Iraq – Implications for travellers
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Publication Date
Mon Jun 08 2020
Journal Name
Medical Sciens
COVID-19 clinical characteristics and outcomes in 60 hospitalized Iraqi patients -Case series
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Background: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Short Text Semantic Similarity Measurement Approach Based on Semantic Network
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Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Intelligent Systems And Internet Of Things
Enhancing Convolutional Neural Network for Image Retrieval
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With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
COVID-19 and Alimentary Tract: Current Evidence and Recent Recommendations
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The pandemic of coronavirus disease 2019 (COVID-19), first reported in China, in December 2019 and since then the digestive tract involvement of  COVID-19 has been progressively described. In this review, I summed recent studies, which have addressed the pathophysiology of COVID-19-induced gastrointestinal symptoms, their prevalence, and bowel pathological and radiological findings of infected patients. The effects of gut microbiota on SARS-CoV-2 and the challenges of nutritional therapy of the infected patients are depicted.  Moreover, I provide a concise summary of the recommendations on the management of inflammatory bowel disease, colorectal cancer, and performing endoscopy in the COVID era. Finally, the COVID pancreatic re

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
Images of Woman, She-Camel and Horse and Their Manifestations in Tarafah-ibnulAbd's Poetry between Symbolic Reference and Poetic Function
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This paper tries to understand the poetic reference in the images of woman, she-camel, horse and their manifestations in Tarafah-ibnulAbd's poetry. There has got my attention the fact that these three images have their own distinct taste which is characterised by a clear rhythm, let alone the  lively nature that is filled with liveliness and activity to be in harmony with the poet's youth. For these three images represented the best manifestations of his psychological and artistic poetics. The paper adopts an artistic analysis to arrive at the psychological aspects of these experiences-the woman, the she-camel, and the horse- and to understand the functions of their images and symbolic reference.

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Publication Date
Sun Feb 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Diagnosing the information technology (IT) capabilities and It’s Effect to Achieving A competitive Superiority Analytical Research in Baghdad soft drinks Company/Al- Zafaraniya
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Purpose: The current research attempts to diagnosis the reflection level of Information Technology (IT) Capabilities (Architectural, infrastructure, human resources, relationships resources, and dynamic capabilities) at Baghdad soft drinks Company/Al- Zafaraniya to achieving the competitive superiority represented by indicators (Cost, quality, flexibility, delivery and innovation). Recognizing the importance of the subjects studied, and because of the importance of the expected results of the field under consideration.

Design/Methodology/Approach: The experimental method has been used, the questionnaire used to collect th

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