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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 Mar 08 2021
Journal Name
Baghdad Science Journal
Effect of growth regulators on responsible rooting for two varieties
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Conducted two trials separate plants Defla first two seasons, 1998 and 1999 to test the susceptibility Altgveria three varieties including Azharha colored white and pink Qati and pink Qtmr and second seasons 1999 and 2000, two types color Azhaarhama white and pink Qati treated mind half-timbered two types of Alaoxinat IBA and NAA and three concentrations as well as repeatersAdhrt results low Almaah rooting

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Publication Date
Sat Nov 12 2016
Journal Name
International Journal Of Mechanical Engineering And Technology (ijmet)
PERFORMANCE OF TWO-WAY NESTING TECHNIQUES FOR SHALLOW WATER MODELS
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A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.

Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Analysis of computer textbooks content for intermediate stage according to the theory of multiple intelligence
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The purpose of current study is to analyze the computer textbooks content for intermediate stage in Iraq according to the theory of multiple intelligence. By answering the following question “what is the percentage of availability of multiple intelligence in the content of the computer textbooks on intermediate stage (grade I, II) for the academic year (2017-2018)? The researcher followed the descriptive analytical research approach (content analysis), and adopted an explicit idea for registration. The research tool was prepared according the Gardner’s classification of multiple intelligence. It has proven validity and reliability. The study found the percentage of multiple intelligence in the content of computer textbooks for the in

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Publication Date
Wed Feb 01 2023
Journal Name
Asian Pacific Journal Of Cancer Prevention
Cytotoxic Activity of the Ethyl Acetate Extract of Iraqi Carica papaya Leaves in Breast and Lung Cancer Cell Lines
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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
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
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
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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