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Diagnosis and Classification of Type II Diabetes based on Multilayer Neural Network
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     Diabetes is considered by the World Health Organization (WHO) as a main health problem globally. In recent years, the incidence of Type II diabetes mellitus was increased significantly due to metabolic disorders caused by malfunction in insulin secretion. It might result in various diseases, such as kidney failure, stroke, heart attacks, nerve damage, and damage in eye retina. Therefore, early diagnosis and classification of Type II diabetes is significant to help physician assessments.

The proposed model is based on Multilayer Neural Network using a dataset of Iraqi diabetes patients obtained from the Specialized Center for Endocrine Glands and Diabetes Diseases. The investigation includes 282 samples, of which 240 are diabetic and 42 are non-diabetic patients. The model consists of three main phases.  In the first phase, two steps are applied as a pre-processing for the dataset, which include statistical analysis and missing values handling. In the second phase, feature extraction is used for diabetes Type II using three main features, reflecting measurements of three blood parameters (C. peptide, fasting Blood Sugar, and Haemoglobin A1C). Finally, classification and performance evaluation are implemented using Feed Forward Neural Network algorithm. The experimental results of the performance of the proposed model showed 98.6% accuracy for diabetes classification.

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Deep Learning of Diabetic Retinopathy Classification in Fundus Images
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Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Comparison of Performance Metrics Level of Restricted Boltzmann Machine and Backpropagation Algorithms in Detecting Diabetes Mellitus Disease
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Diabetes is a disease caused by high sugar levels. Currently, diabetes is one of the most common diseases in the number of people with diabetes worldwide. The increase in diabetes is caused by the delay in establishing the diagnosis of the disease. Therefore, an initial action is needed as a solution that requires the most appropriate and accurate data mining to manage diabetes mellitus. The algorithms used are artificial neural network algorithms, namely Restricted Boltzmann Machine and Backpropagation. This research aims to compare the two algorithms to find which algorithm can produce high accuracy, and determine which algorithm is more accurate in detecting diabetes mellitus. Several stages were involved in this research, including d

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Publication Date
Thu May 05 2022
Journal Name
Al-kindy College Medical Journal
Comparative Study on the Corneal Endothelial Cell Count between Type 2 Diabetic and Non-Diabetic Patients
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Background: Diabetes mellitus is one of the commonest chronic disorders worldwide with a rapid rise in prevalence. In Iraq its prevalence is high especially in elderly age group. Patients with type 2 diabetes mellitus have higher vulnerability for complications, whether microvascular or macrovascular. Ocular complications are common in diabetes mellitus, and comprise diabetic retinopathy, diabetic papillopathy, cataract, glaucoma, dry eye disease and diabetic keratopathy. Diabetic keratopathy involves endothelial and epithelial tissues of the cornea, leading to persistent epithelial defect, corneal erosion, or corneal ulcers.

Aim of the Study: To compare the mean corneal endothelial cell count between patients wi

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis, Characterization and Thermal Analysis of Cu (II), Co (II), Ru(III) and Rh(III) Complexes of a New Acidic Ligand
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Hippuric acid and 3-amino phenol were used to make the 4-(2-Amino-4-hydroxy-phenylazo)-benzoylamino-acetic acid diazonium salt, a new Azo molecule that is a derivative of the (4-Amino-benzoylamino)-acetic acid diazonium salt. We found out what the ligand's chemical structures were by using information from 1HNMR, FTIR, CHN, UV-Vis, LC-mass spectroscopy, and thermal analyses. To make metal complexes of the azo ligand with Co(II), Cu(II), Ru(III), and Rh(III) ions, extra amounts of each azo ligand were mixed with metal chloride salts in a 2:2 mole ratio. The stereochemical structures and geometries of the metal complexes that were studied were guessed based on the fact that the ligand exhibited tetradentate bonding behavior when combined w

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
The effect of Glycated Haemogloin A1c and Fasting Blood Glucose in Type1 Diabetes
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The glycated haemoglobin A1c(HbA1c) and Fasting blood glucose(FBG) effect on type1 diabetic pateints as a screening tests and as a gold standard for assessing glycemic control in subjects with diabetes were studied . Ninety one blood samples were collected in a peroid between June and the end of November 2012 at AL- Kindy Diabetic Center and Central Child Hospital,48 Females and 43 Males , aging between (11 month- 18 year), are divided into three groups, newly diagnosed , ongoing and healthy control group, with duration of disease between(1 day-3months) and (from birth-8 years) for newly diag

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Point of Care testing: The future of periodontal dis-ease diagnosis and monitoring
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Manual probing and periodontal charting are the gold standard for periodontal diagnosis that have been used in practice over a century. These methods are affordable and reliable but they are associated with some drawbacks that cannot be avoided. Among these issues is their reliance on operator’s skills, time-consuming and tedious procedure, lack sensitivity especially in cases of early bone loss, and causing discomfort to the patient. Availability of a wide range of biomarkers in the oral biofluids, dental biofilm, and tissues that potentially reflect the periodontal health and disease accurately encouraged their use as predictive/diagnostic/monitoring tools. Analysing biomarkers during care-giving to the patient using chairside kits i

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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Ebonite linings Based on Natural and Synthetic Rubber
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 The corrosion of metals is of great economic importance. Estimates show that the quarter of the iron and the steel produced is destroyed in this way. Rubber lining has been used for severe corrosion protection because NR and certain synthetic rubbers have a basic resistance to the very corrosive chemicals particularly acids. The present work includes producing ebonite from both natural and synthetic rubbers ; therefore, the following materials were chosen to produce ebonite rubber: a) Natural rubber (NR). b) Styrene butadiene rubber (SBR). c) Nitrile rubber (NBR). d) Neoprene rubber (CR) [WRT]. The best ebonite vulcanizates are obtained in the presence of 30 Pphr sulfur, and carbon black as reinforcing filler. The relation between

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Discrete Optimal Control Mathematical Model of Diabetes Population
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In this work, nonlinear diabetes controlled model with and without complications in a population is considered. The dynamic behavior of diabetes in a population by including a constant control is studied and investigated. The existence of all its possible fixed points is investigated as well as the conditions of the local stability of the considered model are set. We also find the optimal control strategy in order to reduce the number of people having diabetes with complications over a finite period of time. A numerical simulation is provided and confirmed the theoretical results.

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Publication Date
Wed Oct 26 2022
Journal Name
Membranes
Classification of Nanomaterials and the Effect of Graphene Oxide (GO) and Recently Developed Nanoparticles on the Ultrafiltration Membrane and Their Applications: A Review
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The emergence of mixed matrix membranes (MMMs) or nanocomposite membranes embedded with inorganic nanoparticles (NPs) has opened up a possibility for developing different polymeric membranes with improved physicochemical properties, mechanical properties and performance for resolving environmental and energy-effective water purification. This paper presents an overview of the effects of different hydrophilic nanomaterials, including mineral nanomaterials (e.g., silicon dioxide (SiO2) and zeolite), metals oxide (e.g., copper oxide (CuO), zirconium dioxide (ZrO2), zinc oxide (ZnO), antimony tin oxide (ATO), iron (III) oxide (Fe2O3) and tungsten oxide (WOX)), two-dimensional transition (e.g., MXene), metal–organic framework (MOFs), c

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