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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
Tue Jun 15 2021
Journal Name
Al-academy
The directing vision and two display technologies in the Iraqi Child Theater: عباس قاسم كاظم
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  The current research contains four chapters. The first topic included the methodological framework that included the problem of research and the need for it, and then the importance of the research, and then the aim of the research, its limits and the definition of terms linguistically, conventionally and procedurally. The second chapter (the theoretical framework) contained two topics, the topic The first is titled: The Outward Vision in Child Theater Performances, while the second topic was titled: Presentation Technology in Child Theater, Chapter Four (Research Procedures), which organized the research community and analyzed its sample, and the fourth chapter contained research results, conclusions and recommendations. The prop

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Publication Date
Tue Jan 01 2019
Journal Name
In Indian Journal Of Public Health Research And Development
The Significance of p53, Bcl-2, and HER-2/neu Protein Expression in Iraqi Females Breast Cancer Cell Line (AMJ13)
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Publication Date
Fri Dec 01 2023
Journal Name
Experimental And Applied Biomedical Research (eabr)
Correlation Between Ultrasound BI-Rads 4 Breast Lesions and Fine Needle Cytology Categories in a Sample of Iraqi Female Patients
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Breast cancer is the most common malignancy in female and the most registered cause of women’s mortality worldwide. BI-RADS 4 breast lesions are associated with an exceptionally high rate of benign breast pathology and breast cancer, so BI-RADS 4 is subdivided into 4A, 4B and 4C to standardize the risk estimation of breast lesions. The aim of the study: to evaluate the correlation between BI-RADS 4 subdivisions 4A, 4B & 4C and the categories of reporting FNA cytology results. A case series study was conducted in the Oncology Teaching Hospital in Baghdad from September 2018 to September 2019. Included patients had suspicious breast findings and given BI-RADS 4 (4A, 4B, or 4C) in the radiological report accordingly. Fine needle aspirati

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Contribution of Iraqi women in development: from the perspective faculty members to the complex Jadiriyah/University of Baghdad
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The researchers in this study, which aimed to find out Degree contribution of Iraqi
women in development from the perspective faculty members of the complex Jadriya
University in Baghdad, and the the impact of demographic variables (gender, college, place of
living, school level,) for its contribution.
The study population consisted of some faculty members Jadiriyah compound in
Baghdad's University for the academic year 20012/2013. This study followed a descriptive
approach the field, and the analytical method, the study sample consisted of (250) teaching all
of College of Science for girls and education for girls, and to achieve objective of the study
was the development of a questionnaire, was sure of its sincer

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Publication Date
Wed Jan 01 2020
Journal Name
Indian Journal Of Public Health Research & Development
Association of Exon Deletion of MXI1 Gene with Cervical Abnormalities and Cancers Incidence in Some Iraqi Married Women
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ervical cancer is one of the most frequently diag nosed malignancies representing the fourth leading cause of cancer-related death in females’ worldwide, with approximately 500,000 new cases diagnosed and 280,000 deaths occurring each year. Mxi1, an antagonist of c-Myc, maps to human chromosome 10q24-q25, a region altered in a substantial fraction of prostate tumors, in prostate cancer, where a high frequency of loss and mutation of the MXI1 gene has been reported. The aim of present study was to find out the possible association of exon deletion of MXI1 gene with incidence of cervical abnormalities and cancers in some Iraqi married women. The present study include collection of 120 scraping cervical cells samples from women clinically di

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Publication Date
Sat Jan 31 2026
Journal Name
Iraqi Journal Of Community Medicine
Awareness and Expectation of Breast Reconstruction Surgery among Female with Breast Cancer in Baghdad Governorate 2022
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Abstract Background:Breast cancer is the most common female cancer worldwide. Although mastectomy is considered the treatment of choice for the majority of cases of breast cancer; a noticeable percentage of breast cancer survivors claim they were never advised about reconstruction. It has been proven that breast reconstruction helps breast cancer survivors to overcome the trauma of their diagnosis and improve their psychological well-being.Objectives: To assess the level of awareness and expectations regarding breast reconstruction surgery among female with breast cancer survivors in Baghdad, and to find if there is association between sociodemographic data and expectations of breast reconstruction.Methodology: This is a cross sectional stu

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Publication Date
Mon Oct 14 2019
Journal Name
Turkish Journal Of Biology
E2F6 is essential for cell viability in breast cancer cells during replication stress
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Abstract: E2F6 is a member of the E2F family of transcription factors involved in regulation of a wide variety of genes through both activation and repression. E2F6 has been reported as overexpressed in breast cancers but whether or not this is important for tumor development is unclear. We first checked E2F6 expression in tumor cDNAs and the protein level in a range of breast cancer cell lines. RNA interference-mediated depletion was then used to assess the importance of E2F6 expression in cell lines with regard to cell cycle profile using fluorescence-activated cell sorting and a cell survival assay using (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The overexpression of E2F6 was confirmed in breast tumor cDNA samp

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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