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Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>

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Publication Date
Mon Aug 26 2019
Journal Name
Iraqi Journal Of Science
Improving Accuracy in Human Age Classification Using Ensemble Learning Techniques
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     Age is a predominant parameter for arbitrating an individual, for security and access concerns of the data that exist in cyber space. Nowadays we find a rapid growth in unethical practices from youngsters as well as skilled cyber users. Facial image renders a variety of information that can be used, when processed to ascertain the age of individuals. In this paper, local facial features are considered to predict the age group, where local Binary Pattern (LBP) is extracted from four regions of facial images. The prominent areas where wrinkles are developed naturally in human as age increases are taken for feature extraction. Further these feature vectors are subjected to  ensemble techniques that increases th

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Satellite Images Classification in Rural Areas Based on Fractal Dimension
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Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

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Publication Date
Wed Jan 01 2020
Journal Name
Communications In Computer And Information Science
Performance Evaluation for Four Supervised Classifiers in Internet Traffic Classification
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Publication Date
Thu Jan 30 2014
Journal Name
Al-kindy College Medical Journal
Dyslipidemia among patients with type 2 diabetes mellitus visiting Specialized Center for Diabetes and Endocrinology
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Background:The most common pattern of dyslipidemia in diabetic patients is increased triglyceride (TG) and decreased HDL cholesterol level, The concentration of LDL cholesterol in diabetic patients is usually not significantly different from non diabetic individuals, Diabetic patients may have elevated levels of non-HDL cholesterol [ LDL+VLDL]. However type 2 diabetic patients typically have apreponderance of smaller ,denser LDL particles which possibly increases atherogenicity even if the absolute concentration of LDL cholesterol is not significantly increased. The Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP III) and the American Heart Association (AHA ) have designate diabetes as a coronary heart dis

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Study the Effects of Vitamin D as Immune-Modulatory Agent in Type II Diabetes Mellitus Patients
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  This study was designed to show the roles of vitamin D as immune-modulatory agent in serum type II Diabetes Mellitus Patients collected from type II Diabetes Mellitus and controls. They have been classified into two groups as the following: 1) Patients of type II DM group includes (20) individuals from both sexes with age range (35–65) years. 2) Control group: includes (20) healthy individuals from both sexes, with age range (30 – 45) years and no previous disease which may interfere with the parameters analyzed in this research. All the blood samples were analyzed for vitamin D3, albumin, C- reactive protein (CRP), erythrocyte sedimentation rate (ESR), immunoglobulins (IgG, IgM, IgA),  α1- antitrypsin and to

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Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Comparative Study Between The Levels of Adropin in Iraqi Women with Metabolic Syndrome and Diabetes
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By measuring Adropin, fasting blood glucose (FBG), cholesterol, high-density lipoprotein (HDL), triglycerides (TG), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL) in the sera of Iraqi patients with MetS and type 2 diabetes mellitus (T2DM), the current study was designed to compare some crucial markers in metabolic syndrome (MetS) sera and diabetic patients (T2DM) with control. Twenty female subjects were divided into three groups: group I=40 with MetS and group II=40 with T2DM, and 40 healthy subjects were employed as a control group. Compared to the control group, Adropin levels in the Mets group and T2DM group decreased significantly (p < 0.05). In contrast, none of the patient groups (MetS and T2DM)

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Publication Date
Sun Jul 21 2024
Journal Name
Cureus
The Effect of Maternal Blood Glucose on Umbilical Cord Blood Fibrinogen in Women With Gestational Diabetes
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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Color Image Compression of Inter-Prediction Base
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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Semi-Analytical Prediction of Flank Tool Wear in Orthogonal Cutting of Aluminum
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This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The Influence of the Industrial Buyer Behavior on channels of distribution
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Abstract:

This study deals with the influence of the industrial buyer behavior in Channels of distribution. It concentrates on one section of management levels in the company. Which is that of administrative managers The research problem is attempt to study and analysis the influence of industrial buyer behavior in channels of distribution.. The aiming at achieving a number of applicable goals depending on one major hypotheses I set a questionnaire in collecting the data and information relating to the study، which was distributed to sample of ( 30) department manager heads of section states company .  In order to process the data resorted to many statistical methods such as arithmetic means the sta

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