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Diagnostic value of neutrophil lymphocyte ratio in detection of acute appendicitis
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The diagnosis of acute appendicitis (AA) sometimes is illusive and the accompanying clinical and laboratory manifestations cannot be used for definitive diagnosis. Objective: This study aimed to evaluate the diagnostic value of neutrophil/lymphocyte ratio (NLR) in detection of AA. Materials and Methods: This is a cross-sectional study that included a total of 80 adult patients with AA and 62 age- and gender-matched patients with abdominal pain due to causes other than AA. Three milliliter of peripheral blood were collected from each participant. The NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count. Receiver operating characteristic curve was used to assess the diagnostic value of NLR in detection of AA cases. Results: Mean NLR in AA patients was 7.18 ± 2.11 compared with 2.68 ± 1.08 in patients with abdominal pain due to causes other than AA with a highly significant difference. The area under the curve was 0.916 (95%confidence interval = 0.842–0.989), P < 0.001. The sensitivity and specificity of the test at NLR = 4.45 were 90% and 83%, respectively. Conclusions: NLR is an easy, inexpensive test that can be used for AA detection. This test is more sensitive and more specific than either total white blood cell or absolute neutrophil count

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
The effect of liquidity on the profitability and value of banks listed on Iraq stock market (An analytical study)
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  The purpose of the study is to analyze the extent of the impact of liquidity as an independent variable on profitability as an intermediate variable and the value of banks listed in the Iraq Stock Exchange as a dependent variable, as the research problem is summarized by the fact that most banks focus on profitability as a phased goal without focusing on maximizing its value as a strategic goal by enhancing the wealth of owners and shareholders. On the long term, the research community is represented by the banks listed on the Iraq Stock Exchange, while the research sample was deliberately chosen, which included three private banks such as Baghdad Commercial Bank, the Iraqi Commercial Bank and the Iraqi Investment Bank, an

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Practical Study for the Properties of Hueckel Edge Detection Operator
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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease
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Publication Date
Sun Jan 01 2017
Journal Name
Iec2017 Proceedings Book
Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter
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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Science And Research (ijsr)
The Linear Delay Fourth Order Eigen-Value Problems Solved By the Collocation Method
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Accurate Four-Step Hybrid Block Method for Solving Higher-Order Initial Value Problems
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This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Detection of Thrombi in Left Atrial chamber by Transoesophageal Ecchocardiography in patients suffer from Non-rheumatic Atrial Fibrillation
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Background: Background : Patients with non-rheumatic atrial fibrillation have high risk of thromboembolism especially ischemic stroke usually arising from left atrial appendage .Transoesophageal echocardiography provides useful information for risk stratification in these patients as it detects thrombus in the left atrial or left atrial appendage. Objective : This study was conducted at Al-Kadhimiya Teaching Hospital to assess the prevalence of left atrial chamber thrombi in patients with chronic non-rheumatic atrial fibrillation using transoesophageal echocardiography and its clinical significance as well as to verify the superiority of transoesophageal over transthoracic echocardiography in the detection of these abnormalities. Type of

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Publication Date
Wed Mar 28 2018
Journal Name
Indian Journal Of Natural Sciences
Detection of the Main Mycotoxins in Feed of Horses in Al-Zawra'a Park and Study their Effects on Hematological Feature
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Publication Date
Fri Sep 23 2022
Journal Name
Specialusis Ugdymas
Intrusion Detection System Techniques A Review
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With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.