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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 28 2022
Journal Name
Iraqi Journal Of Science
Anti-Mullerian Hormone and Follicle Stimulating Hormone as Markers of Ovarian Agingin a Sample of Iraqi Women
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One-hundred and twenty Iraqi women (60 single women and 60 married women) with age ranges from (17-49) years have been involved in this study to estimate the levels of anti-mullerian hormone (AMH) and follicle stimulating hormone (FSH) as markers of ovarian aging. The descriptive data [age, body mass index (BMI), age at menarche, duration of menarche] have been recorded. Blood samples were collected from the studied women to determine the levels of AMH and FSH.
The results revealed non-significant (p>0.05) differences in levels of AMH and FSH between single women and married women. A significant negative correlation was observed between AMH levels and age in single women (r=-0.519, p<0.05) and married women (r=-0.433, p<0.05)

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Detection of Cytomegalovirus, Rubella virus, and IL-2 Levels in a Sample of Recurrently Aborted Iraqi Women
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The present study aimed to investigate CMV and Rubella virus as a causative agent of recurrent abortion, while the IL-2 levels were estimated as immune parameter during pregnancy period. A total of 63 blood samples were collected from recurrently aborted women, control non-pregnant women and control pregnant women. The results recorded 72.09 % CMV positive aborted women and 27.91 % Rubella virus positive aborted women. Levels of IL-2 were (437.03 ± 38.02) pg/ ml in first group, (390.51± 63.56) pg/ ml in second group, (32.98 ±15.12) pg/ ml in control group non pregnant women and (118.63 ± 24.81) pg/ ml in control pregnant women. High IL-2 levels in all studied women indicate presence of a factor affecting the immune system other than

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Publication Date
Sun May 12 2019
Journal Name
Journal Of The Faculty Of Medicine-baghdad
Level of follicular fluid vitamin D and embryo quality in a sample of Iraqi women undergoing IVF
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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
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
Tue Dec 24 2024
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
Wed Apr 15 2020
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Virulence estimation by calculation of relative expression of NESTIN in different grades of astrocytoma from different age groups of Iraqi patients, extracted from brain tumor stem cells
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Background: Astrocytoma, is heterogeneous tumor of the nervous system and studies on the virulence of these tumors reveal that their behavior is led by small population of cells which are the brain tumor stem cells (BTSCs) that drive the continuous proliferation and self-renewal. From the many markers that annotate BTSCs, are the CD133, and NESTIN.

Objectives: Using CD133, to immunolabel BTSCs niches in paraffin sections of astrocytoma then, extraction of these cells, to calculate fold expression of NESTIN gene across the grades by real time PCR.

Materials and methods: Paraffin blocks of four grades of primary astrocytoma have been selected from three age groups from Iraq

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Publication Date
Sat Oct 22 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Classification of Different Shoulder Girdle Motions for Prosthesis Control Using a Time-Domain Feature Extraction Technique
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Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Use digital classification to follow change detection of al Razzazah sebkha For the period(1976-2013)
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The Sebkha is considered the evaporative geomorphological features, where climate plays an active role. It forms part of the surface features in Mesopotamia plain of Iraqi, which is the most fertile lands, and because of complimentary natural and human factors turned most of the arable land to the territory of Sebkha lands. The use satellite image (Raw Data), Landsat 30M Mss for the year 1976 Landsat 7 ETM, and the Landsat 8 for year 2013 (LDCM) for the summer Landsat Data Continuity Mission and perform geometric correction, enhancements, and Subset image And a visual analysis Space visuals based on the analysis of spectral fingerprints earth's This study has shown that the best in the discrimination of Sebkha Remote sensing techniques a

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