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The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.</p>
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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Association between periodontitis and acquired coronary heart disease
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Background: The association between oral microbial infection and systemic disease is not a new concept. A major confounding issue is that oral infections often are only one of the many important factors that can influence systemic diseases .Objective: This study was conducted to evaluate the periodontal health status of patients with acquired coronary heart disease. Type of the study: Cross-sectional study.Methods: The study group consisted of 200 patients with an age range (35-70) years, having coronary heart disease .This study group were compared to a control group of non-coronary heart disease (200 individuals ) matching with age and gender. The oral parameters were examined including the periodontal conditions, assessment of periodo

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Publication Date
Sat Dec 25 2021
Journal Name
Diyala Journal Of Medicine
Oxidative Stress in Multiple Sclerosis Disease (Review Article)
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Background: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system, in which the myelin sheaths got injured. The prevalence of MS is on grow, as well as, it affects the young ages. Females are most common to have MS compared to males. Oxidative stress is the situation of imbalance between oxidants (free radicals and reactive oxygen species (ROS)) and antioxidants in a living system, in which either the oxidants are elevated or antioxidants are reduced, or sometimes both. ROS and oxidative stress have been implicated in the progression of many degenerative diseases, which is important in cracking the unrevealed mysteries of MS. In this review article, some of the proposed mechanisms that link oxidative stres

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Publication Date
Tue Dec 15 2020
Journal Name
Al-academy
Synthetic Sculpture Techniques in Outputs of Students of the Department of Art Education: أشراق علي خلف العزاوي
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The research studies the synthetic sculpture techniques in the outputs of the students of the department of art education in terms of the shape, texture, content and technique, and employing this style by the students of the department of art education on the college of fine arts, university of Diyala. The research consists of four chapters: the first chapter: the research problem summarized by looking for the synthetic sculpture and its importance in the treatment the industrial wastes in our social life, according to modern synthetic techniques, in the American and European sculpture. This technique has been employed in more than one contemporary artistic direction and style.
This study is considered important for the students of t

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Mon Apr 04 2022
Journal Name
Neuroquantology
The Role of Adropin as a Novel Biomarker in Iraqi Patients with Parkinson's Disease and Osteoporosis
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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
The level of IL-1?, IL-10 and IL-17A in Alzheimer's disease patients: Comparative study
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The objective of this study is to evaluate the level of cytokines IL-1?, IL-10 and IL-17A in the serum of patients with Alzheimer's disease (AD), vascular dementia (VD) and down syndrome (DS). The results showed that Serum level of IL-1? was significantly increased in AD patients (3.79 ± 0.26 pg/ml) as compared with DS patients (2.78 ± 0.39 pg/ml) or controls (2.78 ± 0.22 pg/ml), while no significant difference was observed between AD and VD (3.25 ± 0.20 pg/ml) patients or between VD patients, DS patients and controls. The serum level of IL-10 was approximated in VD and DS patients and controls (3.39 ± 0.24, 2.77 ± 0.39 and 3.41 ± 0.35 pg/ml, respectively), but was significantly (P ? 0.05) increased in AD patients (5.73 ± 0.55 pg/ml

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Publication Date
Sat Apr 02 2022
Journal Name
Neuroquantology
The Role of Neudesin as a Novel Biomarker – in Iraqi Patients with Parkinson's Disease and Osteoporosis
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Neuron-derived neurotrophic factor [NENF], a human plasma neurotrophic factor, also increases neurotrophic activity in conjunction with Parkinson's disease-related proteins in Neudesin. Although Neudesin (neuron-derived neurotrophic secreted protein) is a member of the membrane-associated progesterone receptor (MAPR) protein subclass, it is not evolutionary related to the other members of the same family. The expression of Neudesin is found in both brain and spinal cord from embryonic stages to adulthood, as w Neudesin levels in Parkinson's patients with osteoporosis disease and Parkinson's patients without osteoporosis disease, as well as the relationship between Neudesin levels, Anthropometric and Clinical Features (Age, Gender, BMI) and

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Efficiency Prediction and Performance Characterization of Photovoltaic Solar Panel at Baghdad Climate Conditions
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The performance of a solar cell under sun radiation is necessary to describe the electrical parameters of the cell. The Prova 200 solar panel analyzer is used for the professional testing of four solar cells at Baghdad climate conditions. Voltage -current characteristics of different area solar cells operated under solar irradiation for testing their quality and determining the optimal operational parameters for maximum electrical output were obtained. A correlation is developed between solar cell efficiency h and the corresponding solar cell parameters; solar irradiance G, maximum power Pmax, and production date P. The average absolute error of the proposed correlation is 5.5% for 40 data points. The results also show th

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Publication Date
Wed Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
A Viscoplastic Modeling for Permanent Deformation Prediction of Rubberized and Conventional Mix Asphalt
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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