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Cluster Analysis of Biochemical Markers as Predictor of COVID-19 Severity
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Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patients into two groups(severe cases and non-severe cases groups). Ferritin, lactate dehydrogenase LDH, D-dimer and CRP were markedly increased in COVID-19 patients in the first group (severe cases). Our findings imply that early measured levels of (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) are linked to a decreased probability of COVID-19 severity. Elevated levels of this biomarker may predict COVID severity development.

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Classification & Evaluation of Evidence of deprivation in Iraq (2009) by using Cluster analysis
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       The study aimed to reach the best rating for the views and variables in the totals characterized by qualities and characteristics common within each group and distinguish them from aggregates other for the purpose of distinguishing between Iraqi provinces which suffer from deprivation, for the purpose of identifying the status of those provinces in the early allowing interested parties and regulators to intervene to take appropriate corrective action in a timely manner. Style has been used cluster analysis Cluster analysis to reach the best rating to those totals from the provinces that suffer from problems, where the provinces were classified, based on the variables (Edu

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
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.  T

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Publication Date
Tue Nov 09 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Financial technology as one of the recovery strategies of the Iraqi banking sector in the post-Covid-19 stage: An exploratory study
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The research aims to employ one of the most important strategies for recovery from the crisis of the Covid-19 pandemic, which ravaged the economies of the entire world and its various sectors, including the banking sector, through financial technology that is based on digital transformation to achieve financial sustainability and the creation of innovative financial value chains in light of the decline in the banking sector as a result of The negative effects of the Covid-19 pandemic, be guided by the relevant international accounting standards to control the risks associated with financial technology. To recover from the Covid-19 crisis, the research came out with a set of recommendations, most notably financial technology from

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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 Oct 23 2022
Journal Name
Baghdad Science Journal
Comparison Between Deterministic and Stochastic Model for Interaction (COVID-19) With Host Cells in Humans
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In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

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Publication Date
Tue Jun 01 2021
Journal Name
Political Sciences Journal
The Globalization and the Recruit for Achievement of Marketing Liberalization and the Humanity Ignorant (The Impacts of COVID-19 Pandemic Typical)
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   The emerge of capitalism beside appearing modern and contemporary political systems which had become hold out it is semi-domination on more vital space of human community life, it is through some vital apparatus, which the free market apparatus had make important one which depend on achieve the privileges of the capitalism elite whom standing on it, especially the finance elite. Thus the achievement of the profit had become the main podcasted of those elite which whom the really advancer of the Globalization system, this is which incarnated by the appears and extend of the (COVID-19) fatality pandemic in the end of last year, whereas reveals widespread of it in more than one states in the world, especially the developed coun

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Using Cluster Analysis In Determining The Variables Affecting The Evaluation The Growth Of Children At Different Levels
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In light of the increasing interest in Child-rearing in nurseries and kindergartens and the most important experiences gained by the child at this stage that form the basis for the subsequent stages of her/his physical mental and social growth.

The significance of the research concentrates the need to asses the affecting variables on the child growth to create opportunities for her/him to have intact rearing.

The research also aims to classify these variables at each age level and highlight its moral role.

The problem of the research is the lack of clarity of different variables impact of the child growth in different age levels in nurseries and kindergart

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Publication Date
Sun Jun 27 2021
Journal Name
Journal Of The College Of Education For Women
Persuasive Strategies in WHO COVID-19 Virtual Press Conferences: فراس مجيت حماد , جمعة قادر حسين
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Persuasion is an indispensable skill in everyday life; that is why, it has aroused researchers’ interest. This study aims to investigate the most frequently used persuasive strategies in texting WHO COVID-19 Virtual Press Conferences and explore how these strategies are employed to achieve persuasive messages.To this end, a text of WHO COVID-19 Virtual Press Conferences has been chosen randomly to be analyzed based on Dillard and Shen’s (2013) “Persuasive strategies in Health Campaigns”. A qualitative method has been adopted in analyzing the selected data to investigate the credibility and validity of the persuasive strategies used in such a domain. Findings have shown that most of the persuasive appeals based on the adopted mode

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