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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 Jan 01 2018
Journal Name
Indian Journal Of Public Health Research & Development
Histopathological alternations of placenta in pregnancy women complicated with gestational diabetes
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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Risk factor of urinary incontinence among menopausal women at Babylon city
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Purpose: To identify the risk factors of urinary incontinency for menopausal women.
Methodology: A descriptive analytic study was conducted to identify the risk factor for urinary incontinency
and selected non-probability sample (purposive sample) from (200) menopausal women (45-65) who have
urinary incontinence as visitors and caregiver women who attend at Hila surgical teaching hospital during the
period 1/11/2010-30/3/2011. Questionnaire format used for data collection was designed and constructed
after reviewing related literatures and previous studies and consists of the following variables: Demographic
and reproductive characteristics of menopausal women who suffers from urinary incontinence
Results: The study

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Publication Date
Thu Nov 01 2018
Journal Name
Indian Journal Of Public Health Research & Development
Histopathological changes of placenta in pregnant women complicated with pregestational diabetes
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Publication Date
Sun Mar 01 2015
Journal Name
Baghdad Science Journal
Assessment of Serum Prolactin Level in Patients Women with Rheumatoid Arthritis
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The prolactin hormone played role in the many autoimmune disorders. To determine the importance of high levels of prolactin in triggering rheumatoid arthritis, thirty patient's women with hyperprolactinemia aged (20-45) years old have been investigated and compared with twenty five healthy individuals. All the studied groups were carried out to measure the concentration of citrulinated peptide(CCP) by enzyme linked immunosorbent assay( ELISA), antikeratin antibodies (AKA)and antinuclear antibodies(ANA) by indirect fluorescent assay IFAT. There was a significant elevation of CCP concentration compared with control groups (P< 0.05). The percentage of antikeratin antibodies and antinuclear antibodies was (20%, 10%) respectively, and

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Publication Date
Sun Aug 21 2022
Journal Name
International Journal Of Health Sciences
Effect of x- ray on the treatment of breast cancer combined with amygdalin and doxorubicin separately
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Background: Radiation therapy has the ability to destroy healthy cells in addition to cancer cells in the area being treated. However, when radiation combines with doxorubicin, it becomes more effective on breast cancer treatment. Objective: This study aims to clarify the effect of X-ray from LINAC combined with amygdalin and doxorubicin on breast cancer treatment, and the possibility of using amygdalin with X-ray instead of doxorubicin for the breast cancer treatment. Method: Two cell lines were used in this study, the first one was MCF-7 cell line and second one was WRL- 68 normal cell line. These cells were preserved in liquid nitrogen, prepared, developed and tested in the (place). The effect of three x-ray doses combined with a

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

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Publication Date
Mon Jul 01 2019
Journal Name
Applied Mathematical Modelling
Potential flow of fluid from an elevated, two-dimensional source
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Publication Date
Mon May 04 2009
Journal Name
Journal Of Al-nahrain University
Solution of two-dimensional fractional order volterra integro-differential equations
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In this paper, our aim is to study variational formulation and solutions of 2-dimensional integrodifferential equations of fractional order. We will give a summery of representation to the variational formulation of linear nonhomogenous 2-dimensional Volterra integro-differential equations of the second kind with fractional order. An example will be discussed and solved by using the MathCAD software package when it is needed.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Molecular Typing of Two Suspected Cutaneous Leishmaniasis Isolates in Baghdad
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Leishmaniasis is a group of parasitic diseases caused by Leishmania spp., an endemic infectious agent in developing countries, including Iraq. Diagnosis of cutaneous lesion by stained smears, serology or histopathology are inaccurate and unable to detect the species of Leishmania. Here, two molecular typing methods were examined to identify the promastigotes of suspected cutaneous leishmaniasis samples, on a species level. The first was species-specific B6-PCR and the second was ITS1-PCR followed by restriction fragment length polymorphism (RFLP) using restriction enzyme HaeIII. DNA was extracted from in vitro promastigote culture followed by amplification of kDNA by B6 or amplification and digestion of LITSR/L

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