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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 classification model is divided into three major phases, including pre-processing, training the Resnet-50 network, and classification with evaluation. In the first phase, pre-processing techniques are applied to the APTOS2019 fundus images dataset to find the best features and highlight some fine details of these images. The resnet-50 network was trained in the second phase using the training set and saved the best model obtained that gives high accuracy during the training process. Finally, this saved model has been implemented on the testing dataset for classification DR grades. The proposed model shows good and best classification performance, which was obtained with an accuracy of 98.3%, a precision of 98.4%, an F1-Score of 98.5 % and the recall of 98.4%.

 

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Publication Date
Wed Jan 20 2021
Journal Name
Journal Of Applied Sciences And Nanotechnology
Correlation of MicroRNAs-122a Gene Expression with Diabetic for Iraqi Patients
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This study was carried out to describe the gene expression of the micro RNA 122a gene with the development of diabetes in Iraq. The difference in gene expression between patients and healthy controls was properly considered. In this study, blood was isolated from 121 individuals divided into two groups as follows: 80 samples of diabetic patients and 41 samples from a healthy control. miRNA was isolated and transformed into cDNA, and the expression of mi122a was measured by qRT-PCR. The researchers looked at the relationship between age and gender and the occurrence of diabetes, as well as how they compared to controls. When comparing the mean gene expression level (Ct) of patient groups to the corresponding Ct means in the control group, th

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Publication Date
Fri Aug 29 2014
Journal Name
American Journal Of Pharmacological Sciences
Efficacy and Safety of Ranibizumab Intravitreal Injections versus Laser Photocoagulation in Patients with Diabetic Macular Edema
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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
Erythrocyte Magnesium Levels in type I and type II Iraq diabetic patients effect of antidiabetic treatment
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Background: Direct measurement of intracellular magnesium using erythrocytes has been suggested as a sensitive indicator for the estimation of body magnesium store. Marked depletion in plasma and erythrocyte magnesium levels was particularly evident in diabetic patients with advanced retinopathy and poor diabetic control. While insulin has been shown to stimulate erythrocyte magnesium uptake, hyperglycemia per se suppressed intracellular magnesium in normal human red cells.
Aim of the study: To investigate the erythrocyte magnesium level in Iraqi type I and II diabetic patients, with specific emphasis on the effect of both, metabolic control and the type of antidiabetic treatments.
Methods: Sixty two diabetic patients (7 with type

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of Metformin + Sitagliptin versus Metformin + Glibenclamide on Glycemic Control in Iraqis Type 2 Diabetic Patients
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Combination therapy with a dipeptidyl peptidase–4 inhibitor and metformin or metformin+ glibenclamide results in substantial and additive glucose- lowering effects in Iraqis patients with type 2 diabetes mellitus . This study evaluated the glycemic control by using two groups of  combinations of drugs metformin + glibenclamide and metformin + sitagliptin in Baghdad teaching hospital / medical city. 68 T2DM patients and 34 normal healthy individuals as control group were enrolled in this study and categorized in to two treatment groups. The group 1 (34 patients ) received ( metformin 500 mg three times daily + glibenclamide 5 mg twice daily ) and the group 2 (34 patients) received (metformin 500 mg three times daily + sitaglip

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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Science
Study the Effects of Annona sp. Extract on Some Physiological Parameters and Fertility in Diabetic Mice
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     The current study was conducted to investigate Annona fruit pulp effects on the levels of various physiological biomarkers linked with insulin-dependent diabetes mellitus after disease induction in mice, as well as indications of oxidative stress and male hormones. The rats were separated into four groups, three of which were given Alloxan (90 mg/kg body weight) to induce diabetes, while the fourth served as a negative control. The first group of diabetic mice received no therapy, the second received metformin (600 mg/kg body weight) and the third received Annona fruit puree. The mice were sacrificed at the end of the experiment, to acquire blood and tissue samples from the liver, kidneys and spleen. The first untreated gro

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Effect of L-Carnitine as an Adjuvant Supplement on Lipid Profile in Iraqi Diabetic Patients
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Diabetes is a complex set of diseases require continuous medical care, to control blood sugar and prevent complications is .The aim of this research is to determine the effect of administration of   L carentin to diabetics on the   lipid profile. The research was conducted on sixty diabetic patients were selected from endocrinology and diabetes center / Al-Rusafa, within selected criteria. The patients divided into 3 groups (control group of healthy people and two groups of patients with diabetes who were on metformin and glibenclamide, one group took a L  carnitine in a dose of 1000 mg twice daily and a group dealing with a placebo for a period of 3 months continuously). The study found that patients who took Lc

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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
DETERMINATION OF ADVANCED OXIDATIVE PROTEIN PRODUCTS LEVELS AND ITS CORRELATION WITH INFLAMMATION IN DIABETIC FOOT PATIENTS
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protein oxidation through oxidative stress, which represents the overall status of the protein in the cell/tissue. Due to their increased levels of AOPPs were reported during T2DM. The aim of this study was to assess AOPP level in T2DM subjects with foot ulcer (DFU) and explore its correlation with infection. Type 2 diabetic patients (n=108) and healthy subjects (n=25) were enrolled in this study. The T2DM group was subdivided to diabetic patients without complications (n=25) and eighty-three (83) of them have diabetic foot. They were sub- grouped into two groups according to presence Osteomyelitis and abscess, and in reliance on medical analysis of WBC count and CRP. Group of diabetic without superficial or deep ulcer and no osteomyelitis

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Publication Date
Wed Nov 25 2015
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Subject Independent Facial Emotion Classification Using Geometric Based Features
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Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

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Publication Date
Thu Jan 01 2015
Journal Name
Applied And Computational Mathematics
Texture Classification Using Spline, Wavelet Decomposition and Fractal Dimension
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Publication Date
Tue Dec 31 2024
Journal Name
Journal Of Soft Computing And Computer Applications
Enhancing Image Classification Using a Convolutional Neural Network Model
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In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

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