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Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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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
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
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Fri Jan 15 2021
Journal Name
المجلة العربية للبحوث الادبية والانسانية
Service Leadership and Customer Satisfaction Under COVID-19 Pandemic Crisis : An Empirical Research for Leaders of Public Organizations in Iraq
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The current research aims to identify the degree to which a sample of managers in public organizations appreciated the level of application of the service leadership style from their point of view, and its relationship to the customer satisfaction index in light of the (Covid-19) pandemic, to achieve this, the researcher followed the experimental approach by applying a questionnaire that included two axes, The first: to measure the level of service leadership according to the scale (D. Van Dierendonck and I. Nuijten, 2011), which includes (8) dimensions (empowerment, stand back, accountability, courage, forgiveness, Authenticity, humility, stewardship). The second axis: to measure the level of customer satisfaction according to (Askim, 2004

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Current Potential Options for COVID-19 Treatment in Iraq- Kurdistan Region and the Rest of the World: A Mini-review
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    COVID-19 is an infectious pandemic disease which is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Up to date, scientists are trying to identify a new specific antiviral drug to overcome this disease. Different methods are under study and evaluation in the entire world to control the virus, including blood plasma, blood purification, and antimicrobial and antiviral agents; however, there are no approved drugs yet. This review is focused on the conducted clinical trials worldwide, including the Iraq- Kurdistan region, China, USA, and Europe, to fi

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Publication Date
Sat Feb 18 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Knowledge, Perception, and Reporting Practices of Healthcare Providers about Adverse Events Following the COVID-19 Vaccination in Iraq(Conference Paper )#
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  Routine vaccination activities, such as detection, reporting, and management of adverse events following immunization (AEFIs), are generally handled by healthcare providers (HCPs). Safe vaccines against severe acute respiratory syndrome coronavirus (SARS-CoV-2) were introduced to control the Coronavirus Disease-19 (COVID-19) pandemic. The study aimed to assess the knowledge, perceptions, and practice of HCPs in Iraq about reporting adverse events following COVID-19 vaccination, and their association with sociodemographic variables. The study was a cross-sectional study that was carried out between August and September 2021 at the COVID-19 vaccination centers in Iraq. This study used an online and paper-based questionnaire, which

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
The Modern Techniques in Spatial Analysis to Isolate, Quarantine the Affected Areas and Prevent the Spread of COVID-19 Epidemic
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      COVID-19 is a disease caused by a coronavirus spread globally, including in Iraq; infections have appeared on all Iraq lands in varying proportions. Iraq is among the higher infected world countries. Forty-six infections were simulated on 23 March 2020. Injuries on the eastern side of Baghdad city and to the right side of the Tigris River, which divides the city into two parts, are a natural barrier in quarantine and easily control the movement of people from both sides.

In this study, a model was considered a scientific and practical method by following the steps of identifying infected people using the best scientific approach for the spatial process to prevent the virus from spreading. Remote sensing techniques were

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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Changing the Trends in Surgery during the COVID-19 Times: An Experience from the Eastern Uttar Pradesh State, India: CHANGING TRENDS IN SURGERY DURING COVID TIMES
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Background: The COVID-19 pandemic has an immense effect not only on the social and economic lives of people but also on the surgical lives of surgeons, residents, nursing staff, and patients as well as ground level staff. Amidst this COVID pandemic, emergency surgeries were being done but at a decreased rate, whereas elective cases depended on the will of hospitals, surgeons, and patients. Study aims to promulgate a "Neo–Surgical Check Box" by amalgamating the WHO surgical checklist and the results obtained from the questionnaires.

Subjects and Methods: After receiving ethical clearance from the Institute Ethical Committee, an online questionnaire with 50 questions divided into

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Benchmarking Framework for COVID-19 Classification Machine Learning Method Based on Fuzzy Decision by Opinion Score Method
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     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

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