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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 Jan 18 2024
Journal Name
Journal Port Science Research
Verifying The Association Between IL6 -174G/C Polymorphism in Type 2 Diabetes Mellitus
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Background : Diabetes mellitus, also known as blood sugar, is a series of metabolic disorders described by high blood glucose levels (hyperglycemia), low blood glucose (hypoglycemia), or both, resulting from defects in insulin production, insulin action, or both. Numerous studies have shown that interleukin (IL-6) acts on skeletal muscle cells , liver cells, and pancreas cells to influence glucose balance and metabolism, which directly or indirectly contributes to the development of diabetes. Research in this area is crucial because diabetes is recognized as a major risk factor for many diseases like Diabetic retinopathy, Diabetic nephropathy, Diabetic Neuropathy , heart disease and others.  Patients and methods : In this study, we

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type
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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Prediction of Biodegradability Possibility for Sewage of the Dairy Industry
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2

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Publication Date
Thu Dec 23 2010
Journal Name
Arabian Journal Of Geosciences
Climatic prediction of the terrestrial and coastal areas of Iraq
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Publication Date
Sun Sep 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Study in to the Dynamic Behavior of Packed Distillation Column
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The study of the dynamic behavior of packed distillation column was studied by frequency response analysis using Matlab program. A packed distillation column (80 mm diameter) (2000 mm height) filled with glass packing (Raschig Rings 10mm), packing height (1500 mm) has been modified for separation of methanol-water mixture (60 vol%). The column dynamic behavior was studied experimentally under different step changes in, feed rate (±30%), reflux rate (±22%), and reboiler heat duty (±150%), the top and bottom concentration of methanol were measured. A frequency response analysis for the above step response was carried out using Bode diagram, the log modulus and the phase angle were  used to analyze the process model. A Matlab progra

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Publication Date
Tue Jul 21 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Numerical Study of the Heat Transfer Behavior in Helical Microcoil Tube
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Theoretical and Experimental Study of Corrosion Behavior of Carbon Steel Surface in 3.5% NaCl and 0.5 M HCl with Different Concentrations of Quinolin-2-One Derivative
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A theoretical and protection study was conducted of the corrosion behavior of carbon steel surface with different concentrations of the derivative (Quinolin-2-one), namely 7-Ethyl-4-methyl-1-[(4-nitro-benzylidene)-amino]-1H-quinolin-2-one (EMNQ2O). Theoretically, Density Functional Theory (DFT) of B3LYP/ 6-311++G/ 2d, 2p level was carried out to calculate the geometrical structure, physical properties and chemical inhibition chemical parameters, with the local reactivity in order to predict both the reactive centers and to know the possible sites of nucleophilic and electrophilic attacks, in vacuum and two solvents (DMSO and H2O), all at the equilibrium geometry. Experimentally, the inhibition efficiencies (%IE) in (3.5% NaCl)

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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Publication Date
Sat Jun 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
A novel fusion-based approach for the classification of packets in wireless body area networks
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This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

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Publication Date
Sat Jul 01 2017
Journal Name
Journal Of Construction Engineering And Management
Identification, Quantification, and Classification of Potential Safety Risk for Sustainable Construction in the United States
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