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EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it is obvious that the number of moments selected by the SP should exceed 30% of the overall EEG samples for accuracy to be over 90%.

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Publication Date
Sat Feb 01 2025
Journal Name
Saudi Medical Journal
Spectrum and classification of<i>ATP7B</i>variants with clinical correlation in children with Wilson disease
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Objectives: To study the spectrum and classification of ATP7B variants in Iraqi children with Wilson disease by direct gene sequencing with clinical correlation. Methods: Fifty-five unrelated children with a clinical diagnosis of Wilson disease (WD) were recruited. Deoxyribonucleic acid was extracted from peripheral blood samples, and variants in the ATP7B gene were identified using next-generation sequencing. Results: Seventy-six deleterious variants were detected in 97 out of 110 alleles of the ATP7B gene. Thirty (54.5%) patients had 2 disease-causing variants (15 homozygous and 15 compound heterozygous). Twelve (21.8%) patients had one disease-causing variant and one variant of uncertain significance (VUS) with potential pathogenicity. T

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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
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Sun Dec 31 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
A Ranked-Aware GA with HoG Features for Infant Cry Classification
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Publication Date
Sat Aug 01 2015
Journal Name
2015 Ieee Conference On Computational Intelligence In Bioinformatics And Computational Biology (cibcb)
Granular computing approach for the design of medical data classification systems
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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Classification of brain tumors using the multilayer perceptron artificial neural network
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Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
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The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

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Publication Date
Sun Dec 01 2024
Journal Name
Baghdad Science Journal
Densenet Model for Binary Glaucoma Classification Performance Assessment with Texture Feature
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تعتبر شبكية العين جزءًا مهمًا من العين لأن الأطباء يستخدمون صورها لتشخيص العديد من أمراض العيون مثل الجلوكوما واعتلال الشبكية السكري وإعتام عدسة العين. في الواقع، يعد تصوير الشبكية المجزأ أداة قوية للكشف عن النمو غير العادي في منطقة العين بالإضافة إلى تحديد حجم وبنية القرص البصري. يمكن أن يؤدي الجلوكوما إلى إتلاف القرص البصري، مما يغير مظهر القرص البصري للعين. تعمل تقنيتنا على الكشف عن الجلوكوما وتصنيفه

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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Automatic Computer Aided Diagnostic for COVID-19 Based on Chest X-Ray Image and Particle Swarm Intelligence
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Publication Date
Sat Jan 01 2022
Journal Name
Food Science And Technology
Study on herbicide residues in soybean processing based on UPLC-MS/MS detection
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