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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
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

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Publication Date
Fri Jun 03 2022
Journal Name
Military Medical Science Letters
COVID-19 AMONG A SAMPLE OF IRAQI PATIENTS WITH RHEUMATIC DISEASES: A MULTICENTER STUDY
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Publication Date
Thu Jul 07 2022
Journal Name
Public Works Management & Policy
Impact of Pandemic SARS COVID-19 on Different Construction Project Management: Problems and Solutions
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This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a

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Publication Date
Mon Dec 21 2020
Journal Name
Frontiers In Medicine
Anxiety, Practice Modification, and Economic Impact Among Iraqi Dentists During the COVID-19 Outbreak
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Objectives: As health care workers on the front line during the coronavirus (COVID-19) pandemic, dental practitioners are amongst those at risk due to their close contact with potentially infected individuals. The aim of the current study was to assess the anxiety, awareness practice modification, and economic impact amongst Iraqi dentists whilst working during the outbreak.

Methods: This study was performed using an online survey questionnaire with aid of Google forms from 2nd to 23rd July 2020. A total of 484 clinicians responded. The questionnaire was composed of open end, closed end, and Likert five-point scale questions to assess anxiety, awareness and financial impa

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Publication Date
Sat Dec 05 2020
Journal Name
International Journal Of Clinical Practice
Assessment of COVID‐19 Treatment containing both Hydroxychloroquine and Azithromycin: A natural clinical trial
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Publication Date
Thu Jul 07 2022
Journal Name
Public Works Management & Policy
Impact of Pandemic SARS COVID-19 on Different Construction Project Management: Problems and Solutions
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This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Nurses' Knowledge About Chest Physiotherapy Techniques for Patients With Corona Virus Disease
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Abstract

Objective(s): A descriptive study aimed to determine nurses' knowledge about chest physiotherapy techniques for patients with Corona virus disease and observe the relationship between nurses' knowledge and their socio-demographic characteristics.

Methodology: The study was directed in isolation units of Al- Hussein teaching hospitals in Thi-Qar, Iraq for the period from June 1st,  2022 to November 27th, 2022. Non- probability (purposively) sample comprised 41 nurses. A questionnaire was used for data collection and it consists of two parts: the first part comprises socio demographic features, the second part includes self- administered questionnaire sheet wa

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Publication Date
Sun Jun 27 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Depression among Nurses Providing Care for Patients with COVID-19 at Baqubah Teaching Hospital
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Objectives: The present study aims at detecting the depression among nurses who provide care for infected patients with corona virus phenomenon and to find out relationships between the depression and their demographic characteristics of age, gender, marital status, type of family, education, and years of experience of nurses in heath institutions, infection by corona virus, and their participation in training courses.
Methodology: A descriptive study is established for a period from October 10th, 2020 to April 15th, 2021. The study is conducted on a purposive (non-probability) sample of (100) nurse who are providing care for patients with COVID-19 and they are selected from the isolation wards. The instrument of the study is develope

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Alternative security solutions offered by virtual private network vpn model proposal to use alternatives to Cisco and Microsoft security in al-rasheed bank-delegate general office- northern region
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The study aims to provide a Suggested model for the application of Virtual Private Network is a tool that used to protect the transmitted data through the Web-based information system, and the research included using case study methodology in order to collect the data about the research area ( Al-Rasheed Bank) by using Visio to design and draw the diagrams of the suggested models and adopting the data that have been collected by the interviews with the bank's employees, and the research used the modulation of data in order to find solutions for the research's problem.

The importance of the study Lies in dealing with one of the vital topics at the moment, namely, how to make the information transmitted via

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Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model
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In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

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