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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
Tue Aug 15 2023
Journal Name
Journal Of Economics And Administrative Sciences
Machine Learning Techniques for Analyzing Survival Data of Breast Cancer Patients in Baghdad
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The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

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Publication Date
Thu Mar 07 2024
Journal Name
Problems Of Endocrinology
KI-67 as a predictive indicator of papillary thyroid cancer in Iraqi patients
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BACKGROUND. KI-67 (MKI-67 in humans) is a protein able to bind to DNA which contributes to cell growth and cell proliferation. KI-67 is currently considered as a biomarker that is widely utilized as prognostic indicator for evaluating cell proliferation, diagnosing diseases, and conducting research. Several different kinds of cancer have high Ki-67 expression, which simplifying the choice of treatment for individuals with various cancer types.AIM. The objective was to evaluate the expression of KI67 in patients suffering papillary thyroid cancer (PTC) also the association between patients age and gender and KI67 expression.MATERIALS AND METHODS. To undertake an in-

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Publication Date
Thu Jan 01 2009
Journal Name
Wasit Journal For Science & Medicine
Spectrophotometric Determination of Promethazine Hydrochloride by In (III)
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A simple, rapid and sensitive spectrophotometirc method for the determination of trace amounts of promethazine hydrochloride in the aqueous solution is described. The method is based on the complexation of promethazine hydrochloride with In (III) in the presence of sodium hydroxide to form an soluble product with maximum absorption at 304nm. Beer’s law is obeyed over the concentration range of (2- 20μg/ml) with molar absorptivity of (1.92× 103 L.mol-1 .cm -1 ). The optimum conditions for all development are described and the proposed method has been successfully applied for the determination of promethazine hydrochloride in bulk drug.

Publication Date
Tue Dec 01 2009
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
RECORD OF TWO SPECIES OF THE MONOGENETIC TREMATODES GENUS DACTYLOGYRUS FOR THE FIRST TIME IN IRAQ ON GILLS OF THE CYPRINID FISH ALBURNUS CAERULEUS
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For the first time in Iraq, two species of monogenetic tretamtodes of the genus Dactylogyrus were recorded from gills of Alburnus caeruleus from Tigris river at Al-Zaafaraniya, south of Baghdad during June 1995. The first species, Dactylogyrus sphyrna is characterized by having the seventh pair of marginal hooklets almost twice as large as other marginal hooklets, powerful inner and outer processes of median hooks especially the inner one which is expanded terminally, one connecting bar and long spirally twisted copulatory organ. The second species, Daclytogyrus phoxini differs from the first one by having marginal hooklets of the same size, inner and outer processes of median hooks are not powerful, two connecting bars

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detection capability Alttafaria for some materials using a bacterial mutagenesis system
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Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin

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Publication Date
Wed Jun 24 2015
Journal Name
Chinese Journal Of Biomedical Engineering
Single Channel Fetal ECG Detection Using LMS and RLS Adaptive Filters
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ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

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Publication Date
Thu Apr 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Automatic human ear detection approach using modified adaptive search window technique
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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Hurst Exponent and Tsallis Entropy Markers for Epileptic Detection from Children
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The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

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