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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
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
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
Fri Sep 09 2022
Journal Name
Revista Mexicana De Oftalmología (english Edition)
Posterior subtenon triamcinolone acetonide combined with phacoemulsification for patients with diabetic maculopathy
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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Detection of selected cells in multi choice sheets
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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison Between Two Approaches (MLE &DLS) to Estimate Frechet Poisson Lindley Distribution Compound by Using Simulation
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  In this paper simulation technique plays a vital role to compare between two approaches Maximum Likelihood method and Developed Least Square method to estimate the parameters of Frechet Poisson Lindley Distribution Compound. by coding using Matlab software program. Also, under different sample sizes via mean square error. As the results which obtain that Maximum Likelihood Estimation method is better than Developed Least Square method to estimate these parameters to the proposed distribution.

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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The correlation between CYP2C19 Polymorphisms and recurrent risk in Patients with Ischemic Stroke treated with Clopidogrel in Kurdistan region-Iraq
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    Clopidogrel is a prodrug that must be transformed into an active metabolite by hepatic cytochrome P450 (CYP) isoenzymes to prevent platelet clotting. Polymorphisms of the CYP2C19 gene can cause a reduction or complete loss of CYP2C19 enzyme activity resulting in inhibiting clopidogrel metabolism, effectiveness and increase stroke recurrence risk in ischemic stroke patients. This study aims to investigate the correlation between genetic polymorphisms in CYP2C19*2 and*3 and recurrent risk in patients with ischemic stroke taking clopidogrel 75mg in Kurdistan region –Iraq. This retrospective case-control study was carried out at Kurdistan, Erbil, Medicina medical center, and Rizgary general hospital from January 2021 to

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Publication Date
Sun Sep 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Two Phase Flow in Large Diameter Pipe
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Publication Date
Mon Jul 01 1996
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
TWO PRIMITIVE ORIBATIDS: FIRST RECORD IN IRAQ
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Cosmochthonius reticulatus Grandjean, 1947 (Acari: Oribatei: Cosmochthoniidae) and Rhysotritia ardua ardua C. L. Koch, 1841 ( Acari : Oribate : Euphthiracari¬dae), are two species of oribatids mites first recorded in Iraq from a woodland in the central part of Iraq. The two species are described and illustrated.

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Publication Date
Sun Nov 19 2023
Journal Name
Aip Conference Proceedings
Designing a database for a three dimensional model using geomatics techniques
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Publication Date
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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