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Early Detection of Left Ventricular Systolic Dysfunction in Asymptomatic Patients with Chronic Aortic Regurgitation by two Dimensional Speckle Tracking Echocardiography
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Background: Early detection of subclinical left ventricular (LV) systolic dysfunction is crucial and could influence patients' prognosis by aiding the clinician to candidate patients for better management.

Objective: To detect early LV systolic dysfunction in asymptomatic patient with chronic aortic regurgitation by two dimensional speckle tracking echocardiography.

 Methods:  Sixty one asymptomatic patients with chronic aortic regurgitation, with no ischemic heart diseases (by coronary angiography) or conductive heart diseases, no diabetes mellitus, no hypertension, and no other valvular heart diseases (group 1) and fifty age and sex-matched healthy subjects (group 2) were enrolled into the study. Group (1) was further classified into 3 sub-groups according to 4 chosen parameters from the published guidelines of American Society of Echocardiography (ASE) into: Mild AR, Moderate AR, and Severe AR.

  All patients and controls underwent echocardiographic examination including conventional echocardiography, tissue Doppler study and Two Dimensional (2-D) Speckle Tracking Echocardiography.

Results: GLS showed the highest sensitivity and specificity in detection of subtle LV systolic dysfunction in moderate AR. In moderate AR,a cut off value of > (-19.62) has sensitivity and specificity of 91.3% and 95.5% respectively, with Positive Predictive Value (PPV) and Negative Predictive Value ( NPV ) of 87.5% and 96.9% respectively, Area under curve (AUC) of 0.981. In all types of AR, GLS had higher NPV than PPV which makes it a powerful screening tool for early detection of subtle LV systolic dysfunction.

Conclusion: Global Longitudinal strain measured by 2-D speckle tracking echocardiography is an excellent tool for early detection of subtle LV systolic dysfunction in asymptomatic patients with chronic AR

 

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Publication Date
Wed Oct 18 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Associated Factors with Risk of Relapse in Schizophrenic Patients at Psychiatric Hospitals in Baghdad City
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Schizophrenic patients who are at great risk of relapse are characterized by non-compliance,
denial of illness and need for treatment and no contact with family. So, the prevention of relapse
and readmission to hospital are crucial in mental health practice.
The present study is a descriptive-analytical study that was carried out from November 2nd
2006 through the end of 20 of April 2008.
Objectives: To assess the associated factors with the risk of relapse in schizophrenic patients at
psychiatric hospitals in Baghdad city.
Methodology: A purposive "non-probability" sample of (50) schizophrenic patient who hasd
relapsed was involved in the present study. Data were collected through the use of the constructed
qu

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection
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     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Fri Nov 01 2013
Journal Name
Journal Of Cosmetics, Dermatological Sciences And Applications
Treatment of gray hair in vitiligo patients by direct melanocytes transplant using needling micrografting and dermabrasion techniques
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KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 4

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Publication Date
Mon Dec 23 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluate the Protective Effect of Lactobacillus against Collateral Damage Induced by Ciprofloxacin and Levofloxacin in Iraqi Patients
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Abstract:                                                                                                                Fluoroquinolones drugs are an important class of wide

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

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Publication Date
Thu May 31 2018
Journal Name
International Journal Of Control And Automation
Power Flow Control of Iraqi International Super Grid with Two-Terminal HVDC Techniques Using PSS/E
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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayes Estimators With others , for scale parameter and Reliability function of two parameters Frechet distribution
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