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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 Aug 07 2019
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of the health behaviors patterns among women during pregnancy
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Objective:- Women's behavior during pregnancy which can affect the health of their infant , may be influenced by their attitude toward the pregnancy. The study was carried out to assess the pattern of health behaviors for pregnant women. Methodology: A descriptive study was carried out to select randomized (100) pregnant women attending Baghdad Teaching hospital. The data were collected through personal interview by using questionnaire form constructed for the purpose of the study. Results:- The result of the study revealed that the highest percentage of study sample were in age group (21-25) years, primary graduated and house wife . The results showed that the highest percentage( 64%) of them were primigravida, (72%) of them have (1-2)

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
The effect of the activation functions on the classification accuracy of satellite image by artificial neural network
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Crossref (12)
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Publication Date
Wed Jun 14 2023
Journal Name
Al-academy
The effect of dramatizing characters within the social subject of the basic education stage on student achievement
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The researcher used the experimental approach due to its suitability and the nature of the research problem. The research community was represented by the eighth-grade students in the Rozak Elementary Mixed School affiliated with the General Directorate of Education in Erbil / the center, for the academic year (2021-2022), the number is (96) students, and the research sample consisted of (63) male and female students, with (31) in the experimental group, and (32) in the control group, and (11) students were excluded by (5) students from the experimental group, and (6) students from the control group, as the excluded, are students who failed and were absent from the lessons, and accordingly, the research sample became composed of (52) mal

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Physics: Conference Series
The Bifurcation analysis of Prey-Predator Model in The Presence of Stage Structured with Harvesting and Toxicity
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Abstract<p>For a mathematical model the local bifurcation like pitchfork, transcritical and saddle node occurrence condition is defined in this paper. With the existing of toxicity and harvesting in predator and prey it consist of stage-structured. Near the positive equilibrium point of mathematical model on the Hopf bifurcation with particular emphasis it established. Near the equilibrium point E<sub>0</sub> the transcritical bifurcation occurs it is described with analysis. And it shown that at equilibrium points E<sub>1</sub> and E<sub>2</sub> happened the occurrence of saddle-node bifurcation. At each point the pitch fork bifurcation occurrence is not happened. </p> ... Show More
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Publication Date
Sun Jul 07 2013
Journal Name
Journal Of Educational And Psychological Researches
Effect of Using Computer in Getting and Remaining Information at Students of First Stage in Biology Subject
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Effect of Using Computer in Getting and Remaining Information at Students of First Stage in Biology Subject MIAAD NATHIM RASHEED LECTURER Abstract The recent research goal is to know the influence of computer use to earn and fulfillment information for students of first class in biology material and to achieve that put many of the zeroing hypothesis by researcher as follow: There were no differences between statistical signs at level (0,05) between the average students' marks who they were study by using computer and between the average student ' marks who they were study in classical method of earning and fulfillment. The researcher chose the intentional of the medical technical institute that included of two branches the first class (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
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Beliefs and Their Relationship to Self-Organized Learning Strategies at the Preparatory Stage
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The study aims to identify the level of cognitive beliefs, as well as to identify the level of self-organized learning strategies among intermediate school students. The study also aims to identify the differences in the level of self-organized learning strategies among intermediate school students in term of gender, branch (scientific, literary). In order to achieve the research objectives, the researcher designed a scale to measure the cognitive beliefs. As for the scale of self-organized learning strategies, the researcher adopted a scale of (Pintrich et al. 1991), which was translated by (Izzat Abdelhamid, 1999) , For self-organized learning strategies, the sample consisted of (400) students from the research population, whic

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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
Sun Mar 19 2023
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Absorption and E-learning Readiness in Learning Digitization among Preparatory Stage in Qatar
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Abstract

The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.

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Publication Date
Wed Jan 20 2021
Journal Name
Journal Of Applied Sciences And Nanotechnology
Correlation of MicroRNAs-122a Gene Expression with Diabetic for Iraqi Patients
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This study was carried out to describe the gene expression of the micro RNA 122a gene with the development of diabetes in Iraq. The difference in gene expression between patients and healthy controls was properly considered. In this study, blood was isolated from 121 individuals divided into two groups as follows: 80 samples of diabetic patients and 41 samples from a healthy control. miRNA was isolated and transformed into cDNA, and the expression of mi122a was measured by qRT-PCR. The researchers looked at the relationship between age and gender and the occurrence of diabetes, as well as how they compared to controls. When comparing the mean gene expression level (Ct) of patient groups to the corresponding Ct means in the control group, th

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