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Study of total Immunoglobulin E and Eosinophil count in allergic disease
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The present study aimed to evaluate the levels of total immunoglobulin E and percentage count of eosinophil in some of allergic disease. Blood sample collected from 210 patients (110 female, 100 male) with allergic disease (allergic asthma, allergic rhinitis, and urticaria) their age between 10-70 years and 50 healthy control their age between 23-52 years. A highly significant (P<0.01) increase in the mean serum total IgE in patients with asthma (503.54 ± 63.49 IU/ml), Allergic rhinitis (442.77 ± 95.76 IU/ml) and urticaria (489.53 ± 69.68 IU/ml) as a compared with healthy controls (23.67 ± 5.81 IU/ml).There was a significant difference in percentage count of eosinophil in patients groups allergic asthma 4.37 ± 0.52% ,allergic rhinitis 4.38 ± 0.50%, and urticaria 4.12 ± 0.43% as compared to healthy control 2.57 ± 0.86%. The mean of serum total IgE levels and eosinophil counts may be helpful in the diagnosis of allergic disease.

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Publication Date
Tue Feb 22 2011
Journal Name
Journal Of College Of Education
Partially purification of alanine aminopeptidase from serum of type II diabetic patients with cardiac disease
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This studay was performd on 30 serum specimens of patients having type II diabetes with cardiac disease, and 40 normal specimens were investigated as control group.The activity rate of AAP in patients (125.31± 3.28)I.U/L and activity rate of AAP in normals (6.76±2.21) I.U/L, in addition purification of AAP from serum patients having type II diabetes with cardiac diaease by using dialysis bag and gel filtration (Sephadex G-50). The results of the study reveal that Alanine aminopeptidase (AAP) activity of type II diabetes with cardiac disease patients' serum show a high signifiacant increase (p<0.001) compare to normal subject .

Publication Date
Tue Jul 11 2017
Journal Name
The 39th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc'17)
Higuchi fractal dimension of the electroencephalogram as a biomarker for early detection of Alzheimer's disease
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It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual s

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Publication Date
Fri Jan 24 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Establishment of the possible association between the presence of Helicobacter pylori in the saliva and gastric biopsy by using polymerase chain reaction technique in association with oral manifestation of peptic ulcer disease
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Background: Helicobacter pylori are important gastrointestinal pathogen associated with gastritis, peptic ulcers, and an increased risk of gastric carcinoma. There are several popular methods for detection of H. pylori (invasive and non-invasive methods) each having its own advantages, disadvantages, and limitations, and by using PCR technique the ability to detect H. pylori in saliva samples offers a potential for an alternative test for detection of this microorganism. Materials and methods: The study sample consists of fifty participants of both genders, who undergo Oesophageo-gastrodudenoscopy at the Gastroenterology Department of Al-Kindy Teaching Hospital Baghdad/ Iraq, during five months period from January 2014 to May 2014. They we

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Publication Date
Wed Jan 30 2013
Journal Name
Al-kindy College Medical Journal
Wilson's Disease; Clinical Presentations among Patients Attending Gastroenterology Clinic/ Baghdad Teaching Hospital
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Background:Wilson’s disease (WD) is an inherited
disorder of copper metabolism that is characterized
by tremendous variation in the clinical presentation.
Objective: To assess demographic distribution,
clinical presentations, diagnostic evaluation, and any
association between clinical presentations and other
studied variables of a sample of Iraqi patients with
WD.
Methods: A descriptive cross sectional study with
analytic elements was conducted during 2011, from
the 1st of February till the 10th of June. The sampling
method was a convenient non-random one, carried
out through consecutive pooling of registered WD
patients. A questionnaire-form paper had been
developed for the process of data col

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Pre-operative serum TSH level estimation for predicting malignant nodular thyroid disease
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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Medical Image Classification for Coronavirus Disease (COVID-19) Using Convolutional Neural Networks
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     The coronavirus is a family of viruses that cause different dangerous diseases that lead to death. Two types of this virus have been previously found: SARS-CoV, which causes a severe respiratory syndrome, and MERS-CoV, which causes a respiratory syndrome in the Middle East. The latest coronavirus, originated in the Chinese city of Wuhan, is known as the COVID-19 pandemic. It is a new kind of coronavirus that can harm people and was first discovered in Dec. 2019. According to the statistics of the World Health Organization (WHO), the number of people infected with this serious disease has reached more than seven million people from all over the world. In Iraq, the number of people infected has reached more than tw

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
PFDINN: Comparison between Three Back-propagation Algorithms for Pear Fruit Disease Identification
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     The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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