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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 Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Sat Dec 10 2016
Journal Name
Misan Journal For Physical Education Sciences
Designing and Standardizing two tests for motor coordination timing for youth basketball players
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Designing and Standardizing two tests for motor coordination timing for youth basketball players Research submitted by Prof. Faris sami & asst. prof. Wasan hanoon ali & asst. prof. Feras muttasher Baghdad University-College Of Physical Education and Sport Sciences Motor coordination in basketball is considered one of the most important factors for success in skill performance accuracy and speed due to the defensive and offensive situations of the game. The problem of the research lies in the lack of tests that can specify the growth of motor coordination through which the relative change for a number of players can be noticed due to practice and training. The subjects of the research were (30) young league players of National Center for gif

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Publication Date
Thu May 04 2023
Journal Name
Journal Of Indian Association Of Biomedical Scientists
“Relationship between Cathepsin K and Total oxidative state in diabetes mellitus Iraqi Women patients with osteoporosis
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Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them. Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 normal healthy f

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Publication Date
Thu Nov 06 2025
Journal Name
Pharmacia
Association between maternal vitamin D, calcium, and inflammatory cytokines in Iraqi pregnant women with placental calcification
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Placental calcification is an aging process that is increasingly linked to adverse pregnancy outcomes when it occurs prematurely. Vitamin D has immunomodulatory properties and may play a role in placental calcification. This study explored the association between maternal vitamin D, inflammatory cytokines, and placental calcification. A total of 46 pregnant women aged 16–40 years were included in this study. They were divided into four groups: Group 1 (control group; n = 10, without placental calcification), Group 2 (n = 12, Grade 1 placental calcification), Group 3 (n = 12, Grade 2 placental calcification), and Group 4 (n = 12, Grade 3 placental calcification). Serum vitamin D (25(OH)D) and cytokine (TNF-α,

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Publication Date
Fri Mar 14 2025
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Polycystic Ovary Syndrome and Urinary Tract Stones: A Body Mass Index-Adjusted Analysis in Iraqi Women
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Background: Polycystic ovary syndrome (PCOS) has an unknown and complex etiology. It affects 5–10% of women in the reproductive age. Patients are known to have increased ovarian androgen production that is associated with decreased menses, hirsutism, and acne. Urinary tract stones (UTS) are a multifactorial disorder, with age and sex being known risk factors. Many PCOS patients are obese, and links between nephrolithiasis and obesity have been shown previously. Objectives: To identify the relation between PCOS and UTS considering the patients' body mass index (BMI). Methods: This is a cross-sectional study that enrolled 407 women aged 18-40 who attended the gynecology and obstetrics clinic at Al-Elwiya Maternity Teaching Hospital.

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Publication Date
Sat Sep 21 2024
Journal Name
Asian Pacific Journal Of Cancer Prevention
Oncolytic Newcastle Disease Virus and Photodynamic Therapy as Dual Approach for Breast Cancer Treatment
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Objective: We hypothesized that attacking cancer cells by combining various modes of action can hinder them from taking the chance to evolve resistance to treatment. Incorporation of photodynamic therapy (PDT) with oncolytic virotherapy might be a promising dual approach to cancer treatment. Methods: NDV AMHA1 strain as virotherapy in integration with aminolaevulinic acid (ALA) using low power He-Ne laser as PDT in the existing work was examined against breast cancer cells derived from Iraqi cancer patients named (AMJ13). This combination was evaluated using Chou–Talalay analysis. Results: The results showed an increased killing rate when using both 0.01 and 0.1 Multiplicity of infection (MOI) of the virus when combined with a dose of 617

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Use digital classification to follow change detection of al Razzazah sebkha For the period(1976-2013)
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The Sebkha is considered the evaporative geomorphological features, where climate plays an active role. It forms part of the surface features in Mesopotamia plain of Iraqi, which is the most fertile lands, and because of complimentary natural and human factors turned most of the arable land to the territory of Sebkha lands. The use satellite image (Raw Data), Landsat 30M Mss for the year 1976 Landsat 7 ETM, and the Landsat 8 for year 2013 (LDCM) for the summer Landsat Data Continuity Mission and perform geometric correction, enhancements, and Subset image And a visual analysis Space visuals based on the analysis of spectral fingerprints earth's This study has shown that the best in the discrimination of Sebkha Remote sensing techniques a

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Publication Date
Sat Oct 22 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Classification of Different Shoulder Girdle Motions for Prosthesis Control Using a Time-Domain Feature Extraction Technique
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Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w

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Publication Date
Sun Nov 01 2020
Journal Name
International Journal Of Nonlinear Analysis And Applications
Two Efficient Methods For Solving Non-linear Fourth-Order PDEs
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This paper studies a novel technique based on the use of two effective methods like modified Laplace- variational method (MLVIM) and a new Variational method (MVIM)to solve PDEs with variable coefficients. The current modification for the (MLVIM) is based on coupling of the Variational method (VIM) and Laplace- method (LT). In our proposal there is no need to calculate Lagrange multiplier. We applied Laplace method to the problem .Furthermore, the nonlinear terms for this problem is solved using homotopy method (HPM). Some examples are taken to compare results between two methods and to verify the reliability of our present methods.

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