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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
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region
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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Clinical Dentistry
THE EFFECT OF A PROTECTIVE BARRIER ON THE SHEAR BOND STRENGTH OF DIFFERENT ORTHODONTIC BRACKETS
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Background and objectives: This study aimed at testing the effect of plastic sleeve or barrier, used to cover the guide of the light cure unit to prevent cross-infection, on the shear bond strength and site of bond failure of stainless steel and ceramic orthodontic brackets. Materials and methods: Forty orthodontic brackets; twenty stainless steel and twenty ceramic brackets bonded to forty extracted human maxillary first premolars using light cure adhesive cured with and without the use of a protective plastic barrier on the guide. Comparing the effect of this barrier on the shear bond strength and adhesive remnant index was performed using an independent t-test and Chi-square test. Results: The protective barrier had decreased the shear b

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Publication Date
Fri Dec 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of different curing distances on the microhardness of flowable bulk-fill composite materials
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Background: The microhardness of a composite resin is a vital parameter that is used to determine its clinical behavior. Measuring the microhardness of a composite resin has been used as an indirect method to assess its degree of conversion and extent of polymerization. The purpose of this in vitro study was to evaluate the effect of three curing distances (0, 2, and 4 mm) on the microhardness of the top and bottom surfaces of three types of flowable bulk-fill composite resins (smart dentin replacement, Opus bulk fill flow, and Tetric N). Material and method: Sixty-three specimens from the three types of composite resins (n=21) were fabricated using Teflon mold with a 4mm depth and a 5 mm internal diameter and cured for 20 seconds. For e

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Publication Date
Wed Aug 09 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Optimum Balance Values For Different Coefficients of Spherical Aberration of Optical System Including Different Apertures
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         The optimum balance values for different coefficient of spherical aberration (third and fifth degree also focal shift) were studied, the optical system includes different apertures (circle, ellipse, square and triangle) using point spread function (PSF).       By using (Marechal) method; the minimum value of mean square of variance in wave front was founded, so we can get the maximum of central intensity according to (Strehl) criterion.

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Publication Date
Sun Oct 01 2023
Journal Name
Medical Journal Of Babylon
Prevalence of coronary artery disease in patients with left bundle branch block and its association with risk factors hypertension and diabetes mellitus
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Abstract<sec> <title>Background:

Left bundle branch block (LBBB) is a common finding in electrocardiography, there are many causes of LBBB.

Objectives:

The aim of this study is to discuss the true prevalence of coronary artery disease (CAD) in patients with LBBB and associated risk factors in the form of hypertension and diabetes mellitus.

Materials and Methods:

Patients with LBBB were admitted to the Iraqi heart center for cardiac disea

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Biomechanical Science And Engineering
A COMPARATIVE STUDY OF RETN GENE 3ʹ-UNTRANSLATED REGION POLYMORPHISM RS1862513 IN IRAQI PATIENTS WITH TYPE 1 AND TYPE 2 DIABETES MELLITUS
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Both type 1 diabetes and type 2 diabetes have a genetic component, with over 60 chromosomal regions related to type 1 diabetes and over 200 connected with type 2 diabetes at significant genome-wide levels. Numerous single nucleotide polymorphisms in the RETN gene and genetic variables can account for up to 70% of the variations in circulating resistin levels. The RETN polymorphism has been linked in numerous studies to obesity, insulin sensitivity, type 2 diabetes, and cerebrovascular illness. Our objective is to compare this RETN gene 3ʹ-untranslated region polymorphism in type 1 diabetes and type 2 diabetes Iraqi patients. We choose 51 type 1 diabetes and 52 type 2 diabetes patients against 50 healthy subjects (control group) to investig

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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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