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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 Mar 10 2021
Journal Name
Baghdad Science Journal
Some Immunological Parameters Paraw in Women with vaginal candidiasis
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This study was conducted to know some Immune responses in women with vaginal candidias is by Candidia species. Hemoglubin (Hb) was decreased significantly in patient women comparing with control group. The differential count of Blood cells revealed that neutrophils and monocytcs were increased significantly in patient women comparing with control group. The percentage of the Phagocytosis index was decreased significantly in patient women (66.45 + 15.05) comparing with control group (73.72 + 3.77) and the T- lymphocytes were decreased also in patient women (57.75 + 18.787) comparing with control group (74.25 + 7.759).

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Calculation of Pressure Loss of Two Drilling Muds in Noor Oil Field
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In this work, calculation of pressure losses in circulating system for two drilling muds is evaluated in Noor oil field. Two types of drilling muds that were used for drilling section 12 1/4" and 8 3/4" which are Salt saturated mud and Ferro Chrome Lignosulfonate-Chrome Lignite mud. These calculations are based on field data that were gathered from the drilling site of well Noor-15, which are included, rheological data, flow data and specification of drill string. Based on the obtained results, the best rheological model that fit their data is the Herschel-Bulkley model according to correlation coefficient value for their two drilling mud. Also, the difference between the calculated pressure lo

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Bioequivalence and Pharmacokinetics of Two Formulations of Amlodipine Tablets in Healthy Subjects
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The bioequivalence of a single dose tablet containing 5 mg amlodipine as a test product in comparison to Norvasc® 5 mg tablet (Pfizer USA) as the reference product was studied. Both products were administered to twenty eight healthy male adult subjects applying  a fasting, single-dose, two-treatment, two-period, two-sequence, randomized crossover design with two weeks washout period between dosing. Twenty blood samples were withdrawn from each subject over 144 hours period. Amlodipine concentrations were determined in plasma by a validated HPLC-MS/MS method. From the plasma concentration-time data of each individual, the pharmacokinetic parameters; Cmax, Tmax, AUC0-t, AUC0-

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Publication Date
Mon Sep 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of using Two Binders on the Agglomeration of Zeolite Type 4A
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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
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 May 30 2025
Journal Name
Journal Of Internet Services And Information Security
Enhancing Lung Cancer Classification using CT Images using Processing Techniques Employing U-Net Architecture
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Publication Date
Tue Nov 01 2022
Journal Name
Baghdad Science Journal
Effect of Secondary Metabolite Crude of Metarhizum anisopliea Fungus on the Second Larval Stage of the Housefly Musca domestica
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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Effect of Secondary Metabolite Crude of Metarhizum anisopliea Fungus on the Second Larval Stage of the Housefly Musca domestica
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         The house flies Musca domestica )Diptera:musidae) are the primary carrier of many pathogens such as cholera, typhoid, anthrax, and others. The use of chemical pesticides as a basic method of control leads to many problems at the environmental and health level. The use of safe alternatives to chemical pesticides has become an urgent necessity. The research aims to find biological alternatives that are environment-friendly and non-pathogenic to humans in controlling house flies through the possibility of extracting and diagnosing some secondary metabolites produced by the fungus Metarhizium anisopliae and testing their effects on the second larval stage of house flies using different treatment methods that include

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Publication Date
Wed Oct 06 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Image segmentation by using thresholding technique in two stages
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