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bsj-2862
Detection of BRCA1and BRCA2 mutation for Breast Cancer in Sample of Iraqi Women above 40 Years
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Breast cancer is the commonest cancer affecting women worldwide. Different studies have dealt with the etiological factors of that cancer aiming to find a way for early diagnosis and satisfactory therapy. The present study clarified the relationship between genetic polymorphisms of BRCA1 & BRCA2 genes and some etiological risk factors among breast cancer patients in Iraq. This investigation was carried out on 25 patients (all were females) who were diagnosed as breast cancer patients attended AL-Kadhemya Teaching Hospital in Baghdad and 10 apparently healthy women were used as a control, all women (patients and control) aged above 40 years. The Wizard Promega kit was used for DNA isolation from breast patients and normal individuals. By this method suitable quantities of DNA approximately (50 µl) with purity ranged from (1.7-1.9) were obtained from 100-200µg of fresh biopsy which had been taken from women breast patients. The extracted DNA was successfully used in amplification of BRCA1 & BRCA2 genes by PCR and some mutation were detected. The outcome of genetic analysis indicated that the percentage of 185delAG mutation was 16 (4 patients) whereas, the percentage of 5382insC mutation was 32 (8patients) in BRCA1 gene and the third mutation 6174delT in BRCA2 present in 3 patients only (12%). The study demonstrated that the frequency of BRCA1 mutation (48%) was higher than BRCA2 (12%) in this sample of Iraqi women with breast cancer.

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Publication Date
Tue Oct 04 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
Enhanced Twitter Community Detection using Node Content and Attributes
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Publication Date
Fri Feb 21 2025
Journal Name
2025 First International Conference On Advances In Computer Science, Electrical, Electronics, And Communication Technologies (ce2ct)
Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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Publication Date
Tue Oct 18 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Credit Card Fraud Detection Challenges and Solutions: A Review
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     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c

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Publication Date
Thu Nov 28 2024
Journal Name
Journal Of Emergency Medicine, Trauma And Acute Care
Psychological and sexual problems among women with hysterectomy at Baghdad City
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Hysterectomy is one of the most common gynecological operations done worldwide. Early diagnosis of the psychosexual effects of a hysterectomy and the fast application of appropriate treatment can prevent further worsening and persistence of symptoms, especially with respect to higher levels of anxiety, depression, lower self-esteem, and sexual impact after a hysterectomy. The aim of this study was to assess the psychological and sexual problems of women with hysterectomy. A descriptive study was carried out from March 1, 2023 to May 25, 2023 to determine the level of psychosexual problems experienced by women after hysterectomy. A purposive (non-probability) sample of 120 women who visited the outpatient clinic at Baghdad Teaching H

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Family violence, its causes and effects on society (women and children)
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Summary of the research Family violence, its causes and effects on society (women and children). Search Goal: The current research aims to identify: 1. Causes of family and social violence (for children and women). 2. How to process. research importance : Domestic violence is a major and devastating problem that has a negative and direct impact on children in particular and women or mothers in general. The problem of domestic violence is linked to many factors and individual, social, economic, psychological and environmental variables, which makes one theory that claims to be inaccurate. It is difficult to understand the nature of family violence without linking it to some of the concepts related to it. The negative effects that may lead

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Publication Date
Mon Feb 16 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Dental caries and salivary physiochemical characteristics among osteoporotic old adult women
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Background: Osteoporosis is a systemic skeletal disorder affects general health in addition to effect on salivary physical and chemical composition which lead to an adverse effect on oral health status. This study was conducted to evaluate the concentration of glycoprotein (osteonectin) in saliva and its effect on dental caries in relation to salivary flow rate and viscosity among osteoporotic women and compared to control group. Materials and Methods: The total sample composed of 60 females aged 60-65 years attending Al-Yarmook Teaching Hospital, 30 females diagnosed with osteoporosis by measuring bone density at the spine and femur with a dual-energy X-ray absorptiometry at T-score of >2.5, and 30 women without osteoporosis with T-score o

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