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Two-Stage Classification of Breast Tumor Biomarkers for Iraqi Women
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Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are further classified into either malignant or benign. The collected 20 breast cancer features are utilized to test the performance of the proposed classification system with Leave-One-Out (LOO) cross validation and Synthetic Minority Over-Sampling Technique (SMOTE) to balance the classes. Furthermore, correlation-based feature selection (CFS) was employed in an exploratory analysis to find the best features for the 2-stage classification system.

Results: Classification accuracy of 94% for stage-1 and 100% for stage-2was achieved with a Naïve Bayesclassifier which outperformed other three methods. In addition, CFS selected small subset of features as being the best five features out of the all 20 features for both stage-1 and stage-2.

Conclusion: We achieved a high classification accuracy which is promising to help improve the early diagnosis of breast tumor. The outcome of this study also shows the importance of CA15-3protein in saliva and blood as well as carcinoembryonic antigen level and total protein in blood, and Estrogen hormone level in saliva, for predicting breast tumors.

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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Detection Of Candida Albicans Responsible For Vulvovaginitis In Women
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Background: The vaginal microbial ecosystem stability preclude many other organisms but sometimes the vaginal micro biota is disturbed and this cause change in the normal

balance causing symptoms of vulvuvaginitis like abnormal or increased vaginal discharge, redness and itching.

Objective: To prove C. albicans presence in their vagina clinically and laboratory by culture of vaginal swab on two media.

Type of the study: This study is a case control study

Methods: This study is a case control study in which 100 clinically patient women admitted to maternity hospital in kalar city and khanaqin hospital during the pe

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Publication Date
Sun Jan 01 2017
Journal Name
البحوث التربويةوالنفسية
Preparing a teacher’s guide for computer books for the intermediate stage according to learning styles
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Publication Date
Thu Jun 10 2021
Journal Name
Engineering, Technology & Applied Science Research
Corruption Risk Analysis at the Project Planning Stage in the Iraqi Construction Sector using the Bowtie Methodology
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In this paper, the bowtie method was utilized by a multidisciplinary team in the Federal Board of Supreme Audit (FBSA)for the purpose of managing corruption risks threatening the Iraqi construction sector. Corruption in Iraq is a widespread phenomenon that threatens to degrade society and halt the wheel of economic development, so it must be reduced through appropriate strategies. A total of eleven corruption risks have been identified by the involved parties in corruption and were analyzed by using probability and impact matrix and their priority has been ranked. Bowtie analysis was conducted on four factors with high score risk in causing corruption in the planning stage. The number and effectiveness of the existing proactive meas

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Publication Date
Sun Sep 15 2024
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Biomarkers of Oxidative Stress in Diabetic Microvascular Complications Review Article
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Reactive oxygen species (ROS) are produced as a result of biochemical processes that are not in balance with the body's antioxidant defense mechanism. This metabolic dysfunction is referred to the oxidative stress (OS).  Metabolic dysfunction-associated diseases are affected by changes in the redox balance. It is now widely recognized that oxidative stress significantly affects diabetes mellitus (DM), particularly type 2 diabetes. The biochemical changes associated with  DM could  disturb the oxidative milieu, leading to several microvascular complications in diabetic patients. Thus, DM is a perfect disease to explore the harmful consequences of oxidative stress and how to treat it. Oxidative stress triggered by hyperglycemia is

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Environmental Stress and their relationship to self-rebellion for Preparatory Stage Students
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The Present research aimed at identifying:   

1- The level of environmental stress among preparatory students

2- The level of self-rebellion  among preparatory students

3- The correlation between the two variables of research (environmental stress and self-rebellion) and the extent to which the independent variable contributes to the variable of the middle school students

The current research has determined the students of the fifth stage of the preparatory stage and all the branches in the departments of education in Baghdad province the morning study for the academic

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Publication Date
Wed Nov 18 2020
Journal Name
Medico Legal Update
The Meshing between Epstein Barr Virus Nuclear Antigen-1 and P53 in Iraqi Malignant Breast Tissues
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In Iraq, breast cancer incidence exceeds any other type of cancers and the etiology not understood well.Epstein Barr virus is a gamma herpesviruses and one of carcinogenic viruses that may implicated tobreast carcinogenesis. The nuclear antigen-1 (EBNA-1) protein is the sole EBV antigen that presentedin all tumors related to EBV and plays pivotal roles in carcinogenesis of the virus. Examination appliedby immunohistochemistry (IHC) to detect and demonstrate the correlation between (EBNA-1) and tumorsuppressor protein (P53) expression. The study includes paraffin-embedded tissue blocks of ninety 90malignant breast tissues and thirty 30 normal breast autopsies. EBNA-1 was significantly expressed in 40/90(44.4%) of malignant tissues wh

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Publication Date
Sat Jun 01 2024
Journal Name
Alexandria Engineering Journal
U-Net for genomic sequencing: A novel approach to DNA sequence classification
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Fri Dec 23 2022
Journal Name
F1000research
Association between polymorphisms within the gene coding for tumor necrosis factor (TNF)-alpha with outcomes of treatment in a sample of Iraqi patients with ankylosing spondylitis taking etanercept: an observational study
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Background:Ankylosing spondylitis (AS) is a progressive, chronic inflammatory illness with an unclear etiology that explicitly targets the vertebral column, peripheral joints, and extraarticular tissues. The purpose of this research was to investigate if the existence of single nucleotide polymorphisms (SNPs) in the promoter region of the tumor necrosis factor-alpha (TNF-α) gene at positions -1031T/C (rs199964), -857C/T (rs1799724) and -806C/T (rs4248158) in a sample of Iraqi AS patients could influence the patients' outcomes with etanercept.

Methods:Sixty patients with established AS receiving only etanercept were selected to enroll in this study, with a mean age of 40.75±8.6

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