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Early detection of first degree relatives to type-II diabetes mellitus
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questionnaire was constructed for the purpose of the study, it is composed of (3) major parts, and
overall items, which are included in the questionnaire are (76) items. Reliability and validity of the questionnaire
were determined through a pilot study which is carried out during the period of August, 1
st
, 2008 to February, 30th
2009. The study instrument and structured interview technique were used as means of data collection. The data
were analyzed through the application of the descriptive statistical data analysis approach (Frequency and
Percentage) and the inferential statistical data analysis approach Chi-square, Pearson correlation coefficient.
Results: The results of the study confirmed that the mean of age is (55.7) year, and the majority of the sample are
male, first degree relatives with diabetes mellitus type-II are within positive bio-social aspect and laboratory
screening had an effect on the incidence of diabetes mellitus type-II for first degree relatives to type-II diabetes
mellitus.
Recommendations: The study recommends that the number of diabetes centers should be increased in Baghdad
and Governorates, promote of HbA1c test from general hospitals laboratories, guide notebook about the
predisposing factors of diabetes mellitus in his family, periodic screening for pre-diabetes and diabetes in high risk,
asymptomatic, undiagnosed adults within the health care setting, prevention program to prevent and control on
the predisposing risk factors for nondependent diabetes mellitus type-II and complication

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Detection of Albumin and Urea in Kidney Failure Patients by Optical Biosensor
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The major function of the kidney is the filtration and secretion of the final products of metabolism and the excess of electrolytes. The term kidney failure denotes inability of the kidneys to perform excretory function leading to retention of nitrogenous waste products from the blood. Biosensor are most accurate, with a rapid diagnosis ,more costly method than the traditional method to avoid any biological changes in blood sample that lead to changes optical characteristic (refractive index and absorption) of blood sample. The current study was designed to single mode  more Sensitivity than multi mode for Biomarkers  were recorded for Albumin 5447.06, 5193.93 and Urea sample 2623.14, 1998.44  in sm and mm respectively .

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Detection of Respiratory Syncytial Virus infection in Clinical Samples Using Immunofluorescence Test
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Current study aimed to investigate the Respiratory Syncytial Virus (RSV) in nasal
secretion and throat swab samples of hospitalized patients with symptoms of
respiratory tract infection using Immunofluorescence test. Previously these samples
were tested for Respiratory Syncytial Virus infection by reverse transcriptase-PCR
assay. The positive samples were tested by Immunofluorescence assay in monolayer
confluent of Hep 2 cell line. The results showed that the positive samples using the
RT-PCR test were positive in this test. These results reveal that Immunofluorescence
test is sensitive method for detection the infection with RSV.

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Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
Detection of Sabin Poliovirus Serotypes among Vaccinated Iraqi Children with AFP Syndrom
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Poliomyelitis is a viral disease caused by an enterovirus known as poliovirus and is well known for its role in causing paralysis in children, the virus is only infectious in humans and does pass into the central nervous system and cause various degrees of paralysis, poliovirus passes newcomer disabuse of suppliant to alms-man thumb the fecal-oral route infected persons still shed the virus in their stool allowing the virus to infect others. The main aim of this study was isolating and differentiation of poliovirus strains (Sabin virus) from the stool samples of children received polio vaccine TOPV and suffering from acute flaccid paralysis.

In this study use the cell culture system as the

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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Tue Jan 01 2019
Journal Name
Advances In Public Health
Detection of Antibiotics in Drinking Water Treatment Plants in Baghdad City, Iraq
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Persistence of antibiotics in the aquatic environment has raised concerns regarding their potential influence on potable water quality and human health. This study analyzes the presence of antibiotics in potable water from two treatment plants in Baghdad City. The collected samples were separated using a solid-phase extraction method with hydrophilic-lipophilic balance (HLB) cartridge before being analyzed. The detected antibiotics in the raw and finished drinking water were analyzed and assessed using high-performance liquid chromatography (HPLC), with fluorometric detector and UV detector. The results confirmed that different antibiotics including fluoroquinolones andB-lactams were detected in the raw an

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Publication Date
Mon Jan 30 2023
Journal Name
Iraqi Journal Of Science
Texture Features of Grey Level Size Zone Matrix for Breast Cancer Detection
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    The texture analysis of cancer cells leads to a procedure to distinguish spatial differences within an image and extract essential information. This study used two test tumours images to determine cancer type, location, and geometric characteristics (area, size, dimensions, radius, etc.). The suggested algorithm was designed to detect and distinguish breast cancer using the segmentation-based threshold technique. The method of texture analysis Grey Level Size Zone method was used to extract 11 features: Small Zone Emphasis, Large Zone Emphasis, Low Grey Level Zone Emphasis, High Grey Level Zone Emphasis, Small Zone Low Grey Level Emphasis, Small Zone High Grey Level Emphasis, Large Zone Low Grey Level Emphasis, Large Zone High Gre

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Mon Dec 28 2020
Journal Name
The Iraqi Journal Of Veterinary Medicine
Serological and Molecular Phylogenetic Detection of Coxiella burnetii in Lactating Cows, Iraq
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This study is carried out to investigate the prevalence of Coxiella burnetii (C. burnetii) infections in cattle using an enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) assay targeting IS1111A transposase gene. A total of 130 lactating cows were randomly selected from different areas in Wasit province, Iraq and subjected to blood and milk sampling during the period extended between November 2018 and May 2019. ELISA and PCR tests revealed that 16.15% and 10% of the animals studied were respectively positive. Significant correlations (P<0.05) were detected between the positive results and clinical data. Two positive PCR products were analyzed phylogenetically, named as C. burnetii IQ-No.5 and C. burnet

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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