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MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.

Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Effect of Temperature on the Synthesis of Nano-Gamma Alumina Using Hydrothermal Method
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Nano gamma alumina was prepared by double hydrolysis process using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, hydroxyle poly acid and CTAB (cetyltrimethylammonium bromide) as templates. Different crystallization temperatures (120, 140, 160, and 180) 0C and calcinations temperatures (500, 550, 600, and 650) 0C were applied. All the batches were prepared at PH equals to 9. XRD diffraction technique and infrared Fourier transform spectroscopy were used to investigate the phase formation and the optical properties of the nano gamma alumina. N2 adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the particle size and the

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Publication Date
Fri Jan 13 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Effect of Dapagliflozin on hemoglobin level in heart failure patients with chronic kidney disease and/or diabetes
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Background: Heart failure is a complex clinical syndrome caused by any functional or structural cardiac disease that reduces the ventricle's ability to fill or pump blood. Anemia is frequent in patient with heart failure and is associated with deterioration through the activation of neuro-hormonal pathways. Dapagliflozin is a selective and reversible inhibitor of Sodium-glucose co-transporter-2 (SGLT2). Dapagliflozin increases hemoglobin level through different mechanisms such increasing plasma concentration by diuresis or increasing Erythropoietin synthesis.

Objective: To evaluate the effect of additional dapagliflozin into conventional therapy on hemoglobin in heart failure patients with chronic

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
IoT-Smart Agriculture: Comparative Study on Farming Applications and Disease Prediction of Apple Crop using Machine Learning
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     Recently, the Internet of Things has emerged as an encouraging technology that is scaling up new heights towards the modernization of real word physical objects into smarter devices in several domains. Internet of Things (IoT) based solutions in agriculture drives farming into a smart way through the proliferation of smart devices to enhanced production with minimal human involvement. This paper presents a comprehensive study of the role of IoT in prominent applications of farming, wireless communication protocols, and the role of sensors in precision farming. In this research article, the existing frameworks in IoT-based agriculture systems with relevant technologies are presented. Furthermore, the comparative analysis of the a

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Publication Date
Fri Dec 24 2021
Journal Name
Oncology And Radiotherapy
The effect of different clinicopathological parameters on disease free survival in triple negative breast cancer Iraqi women
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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Evaluation of Some Immunological Markers in Patients with Behcet’s Disease
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The local study were selected 70 Iraqi Arab Patients (39 females and 31 males), who referred to HLA laboratory in teaching laboratories in Baghdad medical city from April 2009 – May 2010 were diagnosed with Behcete's disease, C-reactive protein concentration(CRP) was evaluated by ELISA technique, anti-nuclear antibody (ANA) and anti-neutrophil cytoplasmic antibody (ANCA) were evaluated by Indirect immunofluorescence technology. The result showed significant differences (P<0.05) of CRP concentration in patients group compared with control, negative antinuclear nuclear antibody in all cases while ANCA was positive in 8.5% of patients with type P (PANCA). These results lead to suggest that ANCA auto-antibody may have a role in triggeri

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Association of Circulating MicroRNA-142-3p with Graves Disease
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This study aims to investigate the possible role of circulating microRNA-142-3p (miR-142-3p) in the
development of graves disease (GD) and its association with the antibody directed against thyroid
stimulating hormone receptor (TSHR-Ab) production in patients with GD. Forty patients with positive
TSHR-Ab enrolled in this study were divided ,based on treatment, into (22 untreated (newly diagnosed) and
18 treated patients) and based on family history (30 with positive family history and 10 with negative family
history). In addition to forty healthy subjects with sex and age matching as a control group. The expression
level of circulating miR-142-3p was determined by two steps reverse transcription polymerase c

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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Publication Date
Wed Feb 10 2016
Journal Name
Scientific Reports
Experimental demonstration on the deterministic quantum key distribution based on entangled photons
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As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Reliability Estimation for the Exponential Distribution Based on Monte Carlo Simulation
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        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods

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Publication Date
Wed Jan 01 2020
Journal Name
Communications In Computer And Information Science
Performance Evaluation for Four Supervised Classifiers in Internet Traffic Classification
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