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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
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
Thu Aug 25 2016
Journal Name
International Journal Of Mathematics Trends And Technology
Pretest Single Stage Shrinkage Estimator for the Shape Parameter of the Power Function Distribution
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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
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
Tue Mar 09 2021
Journal Name
Review Of International Geographical Education ( Rigeo )
Social Entrepreneurship and Women Empowerment in The Light of The Corona Pandemic": A Field Study from The Point of View of a Sample of Iraqi Women Entrepreneurs
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This research aims to clarify the conceptual framework of social entrepreneurship shows the importance of the development of social entrepreneurship according to the contextual aspects and the social value achieved from these works. It also identifies the degree of level of a sample of women entrepreneurs in Iraq for the extent of the relationship between social entrepreneurship and women's empowerment. It also explains the impact of entrepreneurial work in empowering women and the extent to which there are individual differences between the average scores of the sample members’ estimation of the level of social entrepreneurship according to social status, age group, educational qualification, and specialization according to the s

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Publication Date
Fri Apr 19 2019
Journal Name
Iraqi Journal Of Biotechnology
Impact of Age Factor in Cervical Abnormalities and Cancers Incidence in Some Iraqi Married Women
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Cervical cancer is the third most common cancer in women worldwide, and it has the fourth highest mortality rate among cancers in women. The present study aimed to reveal the impact of age factor in cervical abnormalities and cancers incidence in some Iraqi married women. 150 scraping cervical cells samples were collected from the women clinically diagnosed with cervical abnormalities and cancer who were divided into two groups; the first group included the women with abnormal pap smear which revealed 13.33% of women were less than 30 years and followed by 66.66% of women whose age between 30-50 years and 20% of them were more than 50 years old. While the second group iclude the women with normal Pap smear (Healthy women) which revealed tha

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
Estimation of Serum Osteocalcin Levels in Osteoporotic Postmenopausal Iraqi Women with Type 2 Diabetes Mellitus
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Background: Osteoporosis (OP) is a systemic disease characterized by low bone mass and micro architectural deterioration of bone tissue, resulting in an increased risk of fractures and has touched rampant proportions. Osteocalcin, one of the osteoblast-specific proteins, showed that its functions as a hormone improves glucose metabolism and reduces fat mass ratio. This study is aimed to estimate the osteocalcin and glucose level in blood serum of osteoporotic postmenopausal Women with and without Type 2 Diabetes.Materials and methods: 60 postmenopausal women with osteoporosis divided into two groups depending on with or without T2DM, 30 patients for each. Serum samples of 30 healthy postmenopausal women were collected as control group. Ost

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Publication Date
Sun Oct 01 2023
Journal Name
Egyptian Journal Of Immunology
Assessment of chemokines MIP-1α and MIP-1 βin Iraqi women with polycystic ovarian syndrome
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Polycystic ovary syndrome (PCOS) is reproductive, endocrine, and metabolic disorder affecting females. The pathology of PCOS is complicated and associated to chronic low-grade inflammation, this includes a disruption in pro-inflammatory factor production, leukocytosis, and endothelial cell dysfunction, also associated with high level of pro-inflammatory cytokines, chemokines and leukocyte count. In addition, PCOS is characterized by hormonal and immunological dysfunction. Inflammation of the ovary affects ovulation and induces or aggravates systemic inflammation. Macrophage inflammatory protein-1 (MIP-1), a pro-inflammatory chemokine, is crucial in the recruitment of inflammatory and immunological cells to the place of inflammation

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Publication Date
Thu Jul 01 2021
Journal Name
International Journal Of Drug Delivery Technology
Association between some risk factors with hormonal state in a sample of infertile iraqi women
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