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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 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
ON-Line MRI Image Selection and Tumor Classification using Artificial Neural Network
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When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Performance quality of single and ?two stage solar concentrators
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The performance of single and two stage solar concentrator were studied ' " The ratio of the primary to the secondary mirrors diameter is taking to be 0.5, depending on the theoretical calculation for the accumulated energy by the concentrator with ratio between 0.0 to 0.9. The design of the systems were designed and examined by using a ray-tracing program. The efficiency of the single and the two stage concentrators are calculated and compared with and without cooling systems.

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Publication Date
Fri Dec 24 2021
Journal Name
Oncology And Radiotherapy
The effect of different clinicopathological parameters on disease free survival in triple negative breast cancer Iraqi women
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Association of potent inflammatory Cytokine and Oxidative DNA Damage Biomarkers in Stomach cancer patients
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The infection with H. Pylori stimulates a signaling cascade that causes the generation of Cytokines and provokes Oxidative stress that is involved in the chronic inflammatory response leads to Gastric cancers. Reactive oxygen species (ROS) produce 8-Hydroxydeoxyguanosine (8-OHdG), the persistent oxidative DNA damage product. The study objective was to assess if there was a link between inflammatory cytokine levels and the presence of Oxidative DNA damage in Gastric tumor patients. In addition, evaluation of the diagnostic and prognostic value of Oxidative DNA damage and inflammatory cytokine biomarkers for Stomach cancers is being conducted. The study was accomplished on medically diagnosed Stomach cancer patients before any form of trea

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
The Numerical Technique Based on Shifted Jacobi-Gauss-Lobatto Polynomials for Solving Two Dimensional Multi-Space Fractional Bioheat Equations
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This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Classification & Evaluation of Evidence of deprivation in Iraq (2009) by using Cluster analysis
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       The study aimed to reach the best rating for the views and variables in the totals characterized by qualities and characteristics common within each group and distinguish them from aggregates other for the purpose of distinguishing between Iraqi provinces which suffer from deprivation, for the purpose of identifying the status of those provinces in the early allowing interested parties and regulators to intervene to take appropriate corrective action in a timely manner. Style has been used cluster analysis Cluster analysis to reach the best rating to those totals from the provinces that suffer from problems, where the provinces were classified, based on the variables (Edu

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Effect of Metformin Treatment on some Blood Biomarkers in Women with Endometriosis.
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 Endometriosis is a common women health disorder that occurs when Endometrial-like tissue grows outside the uterus. This may lead to irregular bleeding , pelvic pain, infertility and other complications.   Metformin,  because of its activity to improve  insulin sensitivity, it is  used for  the treatment of diabetes; it  also  has a modulatory  effect  on  ovarian  steroid  production and has  anti-inflammatory  properties,  all may  suggest  its possible effect in treatment  of endometriosis. This  study  was  planned  to  determine  the  effect  of  metformin  on serum levels  of&nbs

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Publication Date
Mon Jul 06 2020
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Obesity and Breast Cancer: Circulating Adipokines and Their Potential Diagnostic as Risk Biomarkers
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Obesity and cancer are two major epidemics of this century. Obesity is related to a higher risk of many types of cancer. Studies have accessed circulating adipokines, as key-mediators in obesity and breast cancer. The study is aimed to examine the circulating levels of insulin-like growth factor-1, leptin, adiponectin, and resistin in premenopausal Iraqi women with breast cancer. The current study was performed during the period from June 2019 to December 2019 at Oncology unit/ Medical City Hospital-Baghdad. A total of 90 premenopausal women with BC/ stage II and III after 2nd dose of chemotherapy were contributed in this study as patients group. Their ages ranged from (35- 50) years in addition to 90 premenopausal healthy women wer

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Publication Date
Wed Jan 06 2021
Journal Name
Pierm
ULTRA-WIDEBAND FEATURING ENHANCED DELAY AND SUM ALGORITHM AND ORIENTED FOR DETECTING EARLY STAGE BREAST CANCER
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Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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