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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 Dec 23 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Descriptive, Prospective Observational Study- Studying Possible Prediction Factors for Disease Severity and Progression among a Sample of COVD 19 Patients in Iraq
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Abstract

Coronavirus has affected many people around the world and caused an increase in the number of hospitalized patients and deaths. The prediction factor may help the physician to classify whether the patient needs more medical attention to decrease mortality and worsening of symptoms. We aimed to study the possible relationship between C reactive protein level and the severity of symptoms and its effect on the prognosis of the disease. And determine patients who require closer respiratory monitoring and more aggressive supportive therapies to avoid poor prognosis. The data was gathered using medical record data, the patient's medical history, and the onset of symptoms, as well as a blood sample to test the

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Publication Date
Fri Sep 30 2022
Journal Name
International Journal Of Health Sciences
Relation of retinol binding protein4, visfatin and vitamin a in obese and non obese Iraqi patients with non alcoholic fatty liver disease
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One of the most common public liver diseases over the world is fatty liver which contain alcoholic and non-alcoholic fatty liver. One-fourth among general population are impact Non-Alcoholic Fatty Liver Disease (NAFLD) in the worldwide.Retinol binding protein 4 (RBP4) is known as an adipokine, mainly synthesized and secreted from the liver and form adipose tissues. RBP4 acts as a transporter and specifically bound to retinol from liver to others tissues. Visfatin is an adipocytokine and mainly produced from visceral fat tissue, skeletal muscles as well as liver. Vitamin A absorbed, transported as retinyl esters to the liver then hydrolyzed to the retinol form and storage in hepatic stellate cells (HSCs) after reesterified with rigly

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Publication Date
Wed Nov 01 2023
Journal Name
Clinical Epidemiology And Global Health
The association of interleukin-10 single nucleotide polymorphisms (rs1800871) and serum levels in Iraqi patients with celiac disease: A case-control study
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Publication Date
Mon Jan 01 2018
Journal Name
Biochemical Cellular Archive
Immunological and molecular detection of herpes simplex virus type 1 and 2 in patients clinically diagnosed with parkinson’s disease and multiple sclerosis
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To determine the relationship between herpes simplex virus 1, 2 and neurological disorders, sixty samples from patients with neurological diseases were collected (40 patients with Multiple sclerosis and 20 patients with Parkinson’s disease) all of whom attended both the Neurological science Hospital as well as the Neuropathology consultation Department in Baghdad Hospital In Iraq. The samples were collected in the time frame between November 2017 and April 2018. The ages of the patients that were investigated were between (17-76) years and compared to a control group consisting of 25 samples collected from apparently healthy individuals. All the studied groups were subjected to the measurement of anti-HSV 1, 2 IgG antibodies by the means

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Publication Date
Mon Apr 01 2019
Journal Name
Iraqi Journal Of Biotechnology
The Promising Anti-Tumor Impact of Newcastle Disease Virus Expressing IL-2 and P53 Genes in Many Cancer Cell Lines In vitro
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Abstract: Recombinant Newcastle disease virus (rNDV) has shown an anticancer effect in preclinical studies, but has never been tested in a lung cancer models. In this study we explored the anticancer activity of genetically modified NDV expressing IL-2-P53 (rClone30–IL-2-P53) in lung cancer model. We have cloned IL-2 and P53 genes and inserted them in the viral genome of New Castle Disease Virus to create a genetically modified rNDV- IL-2-P53 virus and tested the anti-tumor activity of the new virus in vitro on different types of cancer cell lines by MTT assay. TheIL-2 and P53 gene were successfully cloned and inserted into the viral genome by using a Mlu I and Sfi I endonucleases, viral vector was constructed correctly and successf

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Publication Date
Sun Oct 01 2023
Journal Name
Medical Journal Of Babylon
Prevalence of coronary artery disease in patients with left bundle branch block and its association with risk factors hypertension and diabetes mellitus
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Abstract<sec> <title>Background:

Left bundle branch block (LBBB) is a common finding in electrocardiography, there are many causes of LBBB.

Objectives:

The aim of this study is to discuss the true prevalence of coronary artery disease (CAD) in patients with LBBB and associated risk factors in the form of hypertension and diabetes mellitus.

Materials and Methods:

Patients with LBBB were admitted to the Iraqi heart center for cardiac disea

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Publication Date
Tue Dec 09 2025
Journal Name
Journal Of Al-farahidi’s Arts
Artificial Intelligence Applications in Machine Translation and Their Role in Bridging Semantic Gaps Across Languages: A Comparative Analytical Study of Chat GPT and Deep Seek
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With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology &amp; Innovation
The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Use The moment method to Estimate the Reliability Function Of The Data Of Truncated Skew Normal Distribution
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The Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,

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