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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 disease, in addition to using the classification of the regression tree as well as the use of the genetic algorithm to improve the classification accuracy of both methods and by comparing the methods used to find out the most efficient methods of classification through criteria. Classification error, mean square root error, and average absolute relative error, and concluded that the experimental results are that the methods are good in terms of classification, as they gave results with less classification of error, and that the radial basis network was superior to the classification regression tree, and that the addition of the genetic algorithm led to an improvement classification accuracy.

Paper type: Research paper.

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

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Publication Date
Wed Aug 31 2022
Journal Name
International Review On Modelling And Simulations (iremos)
Inexpensive DC to AC Inverter Device for Artificial Saline Soils Resistivity Analysis
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In aired and semiarid areas like Iraq, saline soil may be considered one of the major concerns. In addition to environmental effects, they may produce significant geotechnical hazards that could interrupt the structure stability depending on the salt type and its concentration. So, it is crucial to identify the degree of the soil salinity with a proper tool for getting a qualified assessment and consequently offering a suitable treatment. In this paper, the electrical resistivity technique has been employed to detect the degree of soil salinity by considering a new electronic system. The system used a single-phase Direct Current (DC) to Alternating Current (AC) inverter accompanied by a transformer. Natural soils became artificially saline

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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Epidemiological Study of Viral Hepatitis/ Chibayish Marsh Reality in Iraq
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Total of 170 samples were collected from Al-Chibayish Marsh reality in Dhi-Qar governorate southern of Iraq to study the epidemology of viral hepatitis in these areas and to detect the type of hepatitis viruses which include A ,B,C,D .The percentage of hepatitis A was 1.17% and most of them below age of ?10 (66.6%) while infection with hepatitis B account 5.29% and includes all age groups. There was no detected cases of hepatitis C,D. The laboratory study showed that the incidence of hepatitis B higher in male (4.11%) compared to female ( 2.35%)

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Publication Date
Tue Apr 05 2011
Journal Name
Global Journal Of Health Science
Analysis of Acute Viral Hepatitis (A and E) in Iraq
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Hepatitis, an inflammation of the liver, has a number of infectious and non-infectious causes. Two of the viruses that cause hepatitis (hepatitis A and E) can be transmitted through water and food; hygiene is therefore important in their control. First, to assess the importance of HAV and HEV as a possible diagnosis for clinically diagnosed patients with acute viral hepatitis. Second, to assess the prevalence of hepatitis A and E in all provinces of Iraq and study its association with age, gender. This study consisted of two groups: The first group consisted of 2975 patients with a clinical diagnosis of acute viral hepatitis. The second group consisted of a total of 9610 persons, which were recruited by surveying a nationally representative

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparative Study for the Early Detection of the most Important Factors Leading to Preeclampsia
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The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla

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Publication Date
Sat Jul 20 2024
Journal Name
Sumer Journal For Pure Science
Classify the Nutritional Status of Iraqi children under Five Years Using Fuzzy Classification
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Publication Date
Wed May 01 2013
Journal Name
Ieee Journal Of Biomedical And Health Informatics
Classification of Finger Movements for the Dexterous Hand Prosthesis Control With Surface Electromyography
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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Sat Jul 18 2026
Journal Name
Journal Of Baghdad College Of Dentistry
A comparative study to evaluate the shear bond strength of different resin sealers to dentin (An in vitro study)
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Background: One of the major problems in endodontics is micro-leakage of root canal fillings which might contribute to the failure of endodontic treatment. To avoid this problem, a variety of sealers have been tested. The objective of this, in vitro, study was to evaluate the shear bond strength of four resin based sealers (AH plus, silver free AH26, RealSeal SE and Perma Evolution permanent root canal filling material) to dentin. Materials and Methods: Forty non-carious extracted lower premolars were used. The 2mm of the occlusal surfaces of teeth were sectioned, to expose the dentin surface. The exposed dentin surfaces of teeth were washed with 5ml of 2.5% NaOCl solution followed by 5ml of 17 % EDTA then rinsed by deionized water to remov

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