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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
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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Publication Date
Thu Mar 31 2022
Journal Name
Psychological Science
The health and social repercussions of the epidemic crisis (Covid-19) on women (An exploratory study for some private universities - Baghdad / Karkh)
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The current research aims to first - reveal the social repercussions of COVID-19 on women A - The impact of the epidemiological crisis on the social structure of the family B - Psychological and social pressures that women are exposed to during the Covid pandemic C - Social isolation resulting from the injury of a member Second - Understanding the health consequences of COVID-19 on women A- Mechanisms of differentiation in the treatment of Covid-19 treatment, home or hospital As for the limits of the research, the current research is determined by some private universities of students, female employees and teaching staff in Karkh district, which number eight (Al-Hikma, Al-Farahidi, Al-Farabi, Tigris, AlTurath, Al-Rashid, Al-Mashreq, Al-Nuso

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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
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
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
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
Thu May 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Mammographic Doses Measurement for A Thick Compressed Breast and the Relationship Between Them
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   This study was done in Baghdad teaching Hospital by using developed instrument type GIOHO and included a number of patients with compressed breast thickness (7,8,9,10)cm .

          The relationship between radiation dose and breast thickness was linear.  All results were compared with the international standered values that measured by the International Nuctear Agency and Europeon sources ,it was found that it is in consistance or has a little difference .

         The study showed that the mean absorbed dose may be determined by using TLD measurement below 10 mGy and the glandular dose was (1.45 mGy) and this can not b

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Publication Date
Thu May 15 2025
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
Tue Nov 09 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Financial technology as one of the recovery strategies of the Iraqi banking sector in the post-Covid-19 stage: An exploratory study
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The research aims to employ one of the most important strategies for recovery from the crisis of the Covid-19 pandemic, which ravaged the economies of the entire world and its various sectors, including the banking sector, through financial technology that is based on digital transformation to achieve financial sustainability and the creation of innovative financial value chains in light of the decline in the banking sector as a result of The negative effects of the Covid-19 pandemic, be guided by the relevant international accounting standards to control the risks associated with financial technology. To recover from the Covid-19 crisis, the research came out with a set of recommendations, most notably financial technology from

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Publication Date
Thu May 31 2018
Journal Name
International Journal Of Control And Automation
Power Flow Control of Iraqi International Super Grid with Two-Terminal HVDC Techniques Using PSS/E
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