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The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.</p>
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Publication Date
Thu Feb 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Knowledge, Attitudes, Practices, and Online Distance Learning Experience of Malaysian University Students towards COVID-19: A Cross Sectional Study(Conference Paper )#
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Some new norms need to be adapted due to COVID-19 pandemic period where people need to wear masks, wash their hands frequently, maintain social distancing, and avoid going out unless necessary. Therefore, educational institutions were closed to minimize the spread of COVID-19. As a result of this, online education was adapted to substitute face-to-face learning. Therefore, this study aimed to assess the Malaysian university students’ adaptation to the new norms, knowledge and practices toward COVID-19, besides, their attitudes toward online learning. A convenient sampling technique was used to recruit 500 Malaysian university students from January to February 2021 through social media. For data collection, all students

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Publication Date
Thu Mar 31 2022
Journal Name
Psychological Science
The health and social repercussions of the epidemic crisis (Covid-19) on women (An exploratory study for some private universities - Baghdad / Karkh)
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The current research aims to first - reveal the social repercussions of COVID-19 on women A - The impact of the epidemiological crisis on the social structure of the family B - Psychological and social pressures that women are exposed to during the Covid pandemic C - Social isolation resulting from the injury of a member Second - Understanding the health consequences of COVID-19 on women A- Mechanisms of differentiation in the treatment of Covid-19 treatment, home or hospital As for the limits of the research, the current research is determined by some private universities of students, female employees and teaching staff in Karkh district, which number eight (Al-Hikma, Al-Farahidi, Al-Farabi, Tigris, AlTurath, Al-Rashid, Al-Mashreq, Al-Nuso

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Publication Date
Sun Dec 31 2023
Journal Name
Lark
Digital and pedagogical practices of French as a foreign language in a post-COVID-19 context (The case of the University of Baghdad)
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Publication Date
Wed Jan 12 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Pharmacoeconomics Study for Anticoagulants used for Hospitalized COVID-19 Patients in Al-Najaf Al-Ashraf city –Iraq(Conference Paper )#
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Abstract

Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through eviden

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Publication Date
Sun Oct 30 2022
Journal Name
Revista Iberoamericana De Psicologia Del Ejercicio Y El Deporte
THE EFFECT OF (HIT) TRAINING ON IMMUNE GLOBULINS AND WHITE BLOOD CELLS FOR AMATEUR WEIGHTLIFTERS AFTER THE RETURN OF ACTIVITY FROM THE MANDATORY QUARANTINE FOR THE COVID-19 EPIDEMIC
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The aim of the research is to identify an appropriate training method that raises the levels of immune globulins (IgA, IgM, IgG) and white blood cells and the effect of training by (HIT) method using resistance (weights) as a training curriculum that increases immunity and ensures the continuation of the pills after the return of activity from the stone The response to the Covid-19 epidemic among amateur weightlifters, the researchers relied on the method of trace analysis in an experimental way by conducting a pre-, medial and post-test with the same experimental one agroup on a sample of amateur weightlifters in the Fury private hall for weightlifting and body building in Adhamiya, the number of sample members reached (15 players) who int

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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Multidisciplinary Healthcare
Development and Initial Validation of Stigma Towards Healthcare Providers Working with COVID-19 Patients Scale (S19-HCPs)
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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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Publication Date
Tue Apr 01 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
The Impact of Feature Importance on Spoofing Attack Detection in IoT Environment
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The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Tue Nov 09 2021
Journal Name
Open Access Macedonian Journal Of Medical Sciences
COVID-19 Vaccine Hesitancy and Acceptance among Medical Students: An Online Cross-sectional Study in Iraq
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BACKGROUND: Vaccine hesitancy and reluctant had an important obstacle in achieving protection and population immunity against coronavirus disease 19 (COVID-19). It is essential to achieve high COVID-19 vaccination acceptance rates among medical students and health care workers to provide recommendations and counseling vaccine hesitant population. AIM: This study aims to identify level of COVID-19 hesitancy, attitude, knowledge, and factors that affect vaccination decision. MATERIALS AND METHODS: A cross-sectional study was done among medical students in Al-Kindy College of Medicine, University of Baghdad, Baghdad, Iraq. Data collection was done through an online Google Forms questionnaire during 2021 from 810 medical students.

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