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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
Mon Apr 23 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Determination of Integrinα2 (ITGA2), Progesterone, Prolactin, Estradiol, Zinc and Vitamin C in Serum of Female Iraqi Patients with Breast Cancer
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Back ground: Cancer is the second leading cause of death throughout the world. Breast cancer, is one of the leading mortality reasons in women from Western Countries, in Iraq, breast cancer is the second reason of death After cardiovascular Diseases.

Material and method:

The study was carried out of period from October/2016-january /2017 and  included (90) serum samples for Iraqi women suffered from breast cancer . Samples were divided into two groups ,the first group included (66) patients (females) their age rang (22-55) years which attended to (tumor unit) at medical city educational oncology hospital and Al-Amal Al-Waatanii hospital in Baghdad ,the second group included (38) for

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
The Relation of IGF-1 and Insulin Resistance in a Sample of Iraqi Obese Type 2 Diabetic Patients with Macrovascular Disease
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Type 2 diabetes mellitus(T2DM) is a metabolic disease that is associated with an increased risk for atherosclerosis by 2-4 folds than in non- diabetics. In general population, low IGF-1 has been associated with higher prevalence of cardiovascular disease and mortality .This study aims to find out the relationship between IGF-1 level and other biochemical markers such as Homeostasis Model Assessment insulin resistance(HOMAIR) and Body Mass Index(BMI) in type 2 diabetic patients . This study includes (82) patients (40 females and 42 males) with age range (40-75) years,(34) non obese diabetic patients and (48) obese diabetic patients. The non obese individuals considered

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Detection of Human Remain Using GPR Technique
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    In this work, animal bones with different shapes and sizes were used to study the characteristics of the ground penetrating Radar system wares reflected by these bones. These bones were buried underground in different depths and surrounding media. The resulting data showed that the detection of buried bones with the GPR technology is highly dependent upon the surrounding media that the bones were buried in. Humidity is the main source of signal loss in such application because humidity results in low signal-to-noise ratio which leads to inability to distinguish between the signal reflected by bones from that reflected by the dopes  in the media such as rock .

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Treating Drill Cuttings Waste with Oil Contamination by Microwave Treatment then by Earthworms Technique
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In this research paper, two techniques were used to treat the drill cuttings resulting from the oil-based drilling fluid. The drill cuttings were taken from the southern Rumaila fields which prepared for testing and fixed with 100 gm per sample and contaminated with two types of crude oil, one from Rumaila oilfields with Sp.gr of 0.882 and the other from the eastern Baghdad oilfield with Sp.gr of 0.924 besides contamination levels of 10% ​​and 15% w/w in mass. Samples were treated first with microwave with a power applied of 540 & 180 watts as well as a time of 50 minutes. It was found that the results reached below 1% w/w in mass, except for two samples they reached below 1.5% w/w in mass. Then, the sample of 1.41% w/w in mass,

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Tue Jun 30 2015
Journal Name
Al-kindy College Medical Journal
Major inflammatory patterns of chronic sinonasal diseases and their accompanied anatomical variations; CT scan review
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Background: Because of wide use of Functional Endoscopic Sinus Surgery (FESS) technique in the recent years and basic role of coronal computed tomography (CT) scan in demonstrating the normal drainage route of para-nasal sinuses, identifying the major patterns of inflammatory sinonasal disease and accompanied anatomical variations is essential for appropriate preoperative surgical planning. In review of publisthed literature, there is no data on CT patterns of chronic inflammatory sinonasal disease and their accompained anatomical variations of nose and PNS in our local population.Objectives: was to determine the frequency of CT patterns and variations in patients with sinonasal symptoms.Methods: This was a cross sectional descriptive st

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Computer Sciences And Informatics
Edge Detection Methods: A Review
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This article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discuss

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Eye Detection using Helmholtz Principle
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            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
Image Segmentation for Skin Detection
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Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

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Publication Date
Mon May 14 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Urinary Vitamin-D Binding Protein as an Early Predictor of Diabetic Nephropathyin Type 1 and Type 2 Diabetes
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    Diabetic nephropathy (DN) is the most common microvascular complication that may lead to chronic renal failure in diabetic patients. Till now microalbuminuria, with its restrictions, is the early marker of DN, appeared after the disease exacerbation. Thus, new biomarkers are required to predict the early onset of DN before the appearance of microalbuminuria. The aim of this study is to investigate the possible use of uVDBP in the early prediction of DN. Fifty diabetic patients with DN and 40 diabetic patients without DN for both types of diabetes were enrolled in this study. All patients were tested for uACR, uVDBP (measured by ELISA), and blood HbA1c. The results demonstrated a highly significant elevation of uAC

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