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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 Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Thu Sep 01 2016
Journal Name
2016 8th Computer Science And Electronic Engineering (ceec)
Class-specific pre-trained sparse autoencoders for learning effective features for document classification
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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Sun Jan 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
Evaluation of Interleukin-18 Serum Concentration and Gene Polymorphism (Rs1946518) in A Sample of Type-2 Diabetes Mellitus Patients from Iraq.
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Background Type two diabetes (T2DM) is characterized by insufficient insulin production and secretion. Additionally, the body develops insulin resistance which affects 90–95% of diabetics. Complex cytokines, receptors, genetic pathways, and the immune system are involved in T2DM. Interleukin-18 (IL-18) is one of the inflammatory cytokines associated with Type 2 diabetes. Environmental and genetic variables, including genetic polymorphisms, can increase T2DM risk and its consequences. Single nucleotide gene polymorphisms (SNPs) are important risk factors for diabetes that can be used to find the disease early and treat it better. Objective This study aimed to determine the levels of IL-18 in the serum of Iraqi patients with Type 2 diabetes

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Effect of the Proposed Outlets on the Hydrodynamic Behavior and Water Quality of the South-West Part of the Al Hammar Marsh
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The current study aims to find a new plan to manage the water quality of the western part of the Hammar Marsh to reduce the salts that cause problems for the marshes and preserve their environmental life by isolating the southwestern part of the Hammar Marsh by closing the outlet under the railway embankment. The outlet is discharging saline water to the east-western part of Al Hammar Marsh. After isolating the southwestern part of the marsh, a new outlet is proposed. The impact of the flow hydrodynamics on improving the water quality was simulated using the SMS model. The hydrodynamics and water quality simulation models for the marsh are : a hydrodynamic model and average depth (SMS RMA2) and a two-dimensional water quality model (SMS

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Publication Date
Tue Jan 18 2022
Journal Name
Materials Science Forum
Spatial Analyzing of the Chemical Soil Properties for the Sanam Mountain-Al Zubair Region South of Basra Province and Diagnosis of its Effects on Soil Qualities Using Remote Sensing Technology and GIS
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Publication Date
Tue Jan 18 2022
Journal Name
Materials Science Forum
Spatial Analyzing of the Chemical Soil Properties for the Sanam Mountain- Al Zubair Region South of Basra Province and Diagnosis of its Effects on Soil Qualities Using Remote Sensing Technology and GIS
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The article discusses the spatial analysis of the chemical soil properties that is a key component of the agriculture ecosystem based on satellite images. The main objective of the present study is to measure the chemical soil properties (total dissolved salts (TDS), Electrical conductivity (EC), PH, and) and the ​spatial variability. On 13 November 2020 (wet season), a total of 12 soil samples were collected in the field through random sampling in the Sanam mountain-Al Zubair region south of Basra province, to contain its soil samples components of minerals and precious elements such as silica and sulfur. From experimental results, the soil sample in the sixth position has the highest concentration of TDS values, reached (5798.4

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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Effect of Hydroxyapatite Coatings on Corrosion Behavior for Biotype 316L SS Used in Orthopaedic Applications
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Electrochemical corrosion of hydroxyapatite (HAP) coated performance depends on various parameters like applied potential, time, thickness and sintering temperature. Thus, the optimum parameters required for the development of stable HAP coatings was found by using electrophoretic deposition (EPD) technique. This study discusses the results obtained from open circuit potential-time measurements (OCP-time), potentiodynamic polarisation and immersion tests for all alloy samples done under varying experimental conditions, so that the optimum coating parameters can be established. The ageing studies of the coated samples were carried out by immersing them in Ringer’s solution for a period of 30 days indicates the importance of stable HAP c

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