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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 30 2021
Journal Name
Al-kindy College Medical Journal
Diagnostic Evaluation of Uterine Artery Doppler Imaging for the Prediction of Early Abnormal Pregnancy
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Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy.

Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when a

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Publication Date
Sun Dec 31 2000
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Transient Behavior of Straight Fins
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Publication Date
Sat Jan 01 2022
Journal Name
Encyclopedia Of Smart Materials
Modeling Behavior of Magnetorheological Fluids
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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Effects of Allopurinol on Ketone Body Metabolism and Tissue Lipid Peroxidation in Alloxan Diabetes in Rats
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The aim of the present study is to investigate whether or not xanthine oxidase (XO)–derived reactive oxygen species (ROS) may play a role in the pathogenesis of alloxan (ALX)–induced diabetes in rats using the specific XO inhibitor and hydroxyl radical scavenger, allopurinol

The involvement of oxidative stress in ALX – diabetes was assessed by the measurement of plasma and various tissues lipid peroxides levels ( using thiobarbituric acid ( TBA ) reactive substances ). Furthermore, the ability of allopurinol to influence these and other biochemical parameters, including plasma and urine ketones levels were also investigated in diabetic rats.

Rats were divided into four groups: control, untreated diabe

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Publication Date
Sun Jan 01 2023
Journal Name
Medical Journal Of Babylon
Evaluation of the Salivary Levels of Interleukin-17 and Galectin-3 in Patients with Periodontitis and Type 2 Diabetes Mellitus
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Background: Periodontitis and type 2 diabetes mellitus are both considered as a chronic disease that affect many people and have an interrelationship in their pathogenesis. Objective: The aim is to evaluate the salivary levels of interleukin-17 (IL-17) and galectin-3 in patients with periodontitis and type-2 diabetes mellitus. Materials and Methods: The samples were gathered from 13 healthy (control group) and 75 patients split into 3 groups, 25 patients with type 2 diabetes mellitus and healthy periodontium (T2DM group), 25 patients with generalized periodontitis (P group), and 25 patients with generalized periodontitis and type 2 diabetes mellitus (P-T2DM group). Clinical periodontal parameters were documented. The concentration of IL-17

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Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between some of linear classification models with practical application
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Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Two-Stage Classification of Breast Tumor Biomarkers for Iraqi Women
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Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

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Publication Date
Fri Dec 31 2021
Journal Name
Political Sciences Journal
Moderation in Omani External political behavior (1970-2020)
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Receipt date:08/26/2020 accepted date:9/8/2020 Publication date:12/31/2021

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

        The research entitled (Moderation in Omani External Political Behavior 1970-2020. contained introduction and two sections conclusion and recommendations. The introduction included a general overview of the topic, and the importance of the political behavior o

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Publication Date
Wed Dec 13 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of an Educational Program on Nurses' Knowledge Toward Early Prediction of Acquired Weakness in The Intensive Care Unit.
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Abstract:

Objectives: The present study aims to evaluate effectiveness of educational program the nurses' knowledge towards early prediction of acquired weakness in the intensive care unit.

Methodology: A pre-experimental study design (comparison of two groups), which was achieved through the pre and post-test method for the study sample through the application of an educational program in the intensive care unit of Al-Zahra Teaching Hospital in Kut city, Wasit Governorate. The study was conducted for the period from 28th April 2022 to 15th August 2022 by selecting a purposive (non-probability) sample for this study. The study sample size was (52) nu

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