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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
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
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Hematological Parameters as Indicators for Litter size and Pregnancy Stage in Awassi ‎Ewes
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Physiological status and litter size can indeed have a significant impact on ewes' ‎hematological parameters, which are essential indicators of their health. Therefore, this study ‎examined the hematological profiles of ewes during pregnancy with single and twins in the ‎Awassi ewes. The present study involved 232 ewes in good health and at sexual maturity. ‎Among them, 123 ewes had single pregnancies, while 109 ewes had twin pregnancies. The age ‎range of the ewes included in the study was between 3.5 and 4.5 years. Hematological tests ‎were conducted on the sheep's blood samples promptly following collection. The findings ‎demonstrated variations in hematological parameters among pregnant

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Publication Date
Mon Jul 25 2022
Journal Name
International Journal Of Health Sciences
Sequencing of ca-int-l gene of Candida Spp. In infected urinary tract among Iraqi women
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The most common nosocomial fungal infection in hospitals is urinary tract candidiasis. Candida albicans is the most prevalent cause of nosocomial fungal urinary tract infections, however Candida species distribution is changing rapidly. At the same time, the rise in urinary tract candidiasis has resulted in the emergence of antifungal-resistant Candida species. This study aimed to diagnose Candida Spp. In women with UTI and reveal the nucleotides sequences of CA-INT-L Gene to look for mutation within the gene. This study included 100 women patients suffering from urinary tract infections and vaginal swabs samples from those individuals were taken to identify the presence of Candida. They were between the ages of 22 and 67. Candida i

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Publication Date
Wed Dec 30 2015
Journal Name
Journal Of Chemical, Biological And Physical Sciences
Prevalence of Autoimmune Thyroid Disorders in a Sample of Iraqi Infertile Women with Polycystic Ovary Syndrome
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The present study aims to estimating the prevalence of autoimmune thyroid disorders in Iraqi infertile women with polycystic ovary syndrome (PCOS). Eighty-five Iraqi women, with age range (19-45) years, were divided into three groups; first group included 33 women with PCOS; second group included 30 women without PCOS; while third group included 22 fertile women as controls. The clinical data [age, body mass index (BMI), and menstrual status] have been recorded. Blood samples were collected to determine the levels of reproductive hormones [estradiol (E2), luteinizing hormone (LH), and follicle stimulating hormone (FSH)]; and thyroid hormones [triiodothyronine (T3) and thyroxin (T4)]. Also, autoimmune thyroid antibodies assessment h

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Publication Date
Thu Jun 30 2022
Journal Name
International Journal Of Drug Delivery Technology
Expression of Vascular Endothelial Growth Factor in the Placenta of Iraqi Women Complicated with Hypertensive Disorder
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During pregnancy, high blood pressure disorder is the most common medical complication in pregnancy. It is the foremost cause of maternal mortality and perinatal diseases. Vascular endothelial growth factor (VEGF) affects the growth of vascular endothelial cells, existence, and multiplying, which are known to be expressed in the human placenta. This study aimed to identify the expression VEGF in the placenta of hypertension and normotensive women. In this study, a cross-sectional study from november 2019 to February 2020. A total of 100 placentae involved 50 hypertensive cases and 50 normotensive groups were assessed. VEGF-A expression in two placentas groups was evaluated by immunohistochemistry techniques. Strong and moderate VEGF

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Publication Date
Sun Dec 27 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Estimation of Beta Two Microglobulins, Fetuin-A, Resistin Serum Level in Iraqi Multiple Myeloma Patients
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Multiple myeloma is hematological disease produces many complications in the bone, kidney, neural and other complications. The study aims to measure serum biomolecules like fetuin-A and resistin and determined the possibility to use these biomarkers as disease predictor. blood samples were isolated from 58 patients and 24 sex and age-matched control, serum then isolated, and proper ELISA kit then used to a determined level of B2 microglobulin, resistin, and fetuin-A. The result demonstrated significant increase in   B2 microglobulin, fetuin-A and resistin in patients compare to control (1.3470.714 vs. 0.9130.253), p = 0.000, (14.00310.352 vs. 9.2594.264), p= 0.005, (1.9673.595 vs. 0.6040.622), p = 0.009, respectively. &

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Scopus (4)
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Publication Date
Sun Dec 27 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn: 1683 - 3597 , E-issn : 2521 - 3512)
Estimation of Beta Two Microglobulins, Fetuin-A, Resistin Serum Level in Iraqi Multiple Myeloma Patients
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Multiple myeloma is hematological disease produces many complications in the bone, kidney, neural and other complications. The study aims to measure serum biomolecules like fetuin-A and resistin and determined the possibility to use these biomarkers as disease predictor. blood samples were isolated from 58 patients and 24 sex and age-matched control, serum then isolated, and proper ELISA kit then used to a determined level of B2 microglobulin, resistin, and fetuin-A. The result demonstrated significant increase in   B2 microglobulin, fetuin-A and resistin in patients compare to control (1.3470.714 vs. 0.9130.253), p = 0.000, (14.00310.352 vs. 9.2594.264), p= 0.005, (1.9673.595 vs. 0.6040.622), p = 0.009, respectively.   These di

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Publication Date
Fri Jan 30 2026
Journal Name
Al Kut Journal Of Economics And Administrative Sciences
Use of the Bootstrap in the logistic regression model for Breast cancer disease
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The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

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Publication Date
Sat Feb 24 2024
Journal Name
Journal Of Studies And Researches Of Sport Education
The effect of the use of the Colb model according to the two forms (adaptive, ascending) in learning some of the technical skills of women
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The objective of the study was to identify the effect of the use of the Colb model for the students of the third stage in the College of Physical Education and Sports Sciences, University of Baghdad,As well as to identify the differences between the research groups in the remote tests in learning skills using the model Colb.The researcher used the experimental method and included the sample of the research on the students of the third stage in the College of Physical Education and Sports Science / University of Baghdad by drawing lots, the third division (j) was chosen to represent the experimental group,And the third division (c) to represent the control groupafter the distribution of the sample splitting measure according to the Colb mode

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