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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
Sat Jun 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Perineural Invasion in Oral Squamous Cell Carcinoma in Relation to Tumor Depth
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Background: The American Joint committee on Cancer in their 8th edition staging manual regarded perineural invasion as one of the most important prognostic factors for Lip and Oral Cavity Squamous Cell Carcinoma, it also incorporated tumor depth of invasion in defining tumor size category in the new staging system. This study was conducted to evaluate the frequency of perineural invasion in oral squamous cell carcinoma and the effect of approaching tumor depth in this process. Materials and Methods: fifty-four formalin fixed paraffin embedded tissue blocks of radical resections of Oral Squamous Cell Carcinoma were cut and stained with Hematoxylin and Eosin stain, then evaluated for perineural invasion, with estimation of tumor depth of i

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of Employing Microteaching in Acquiring Teaching Skills for Students Teaching The Basic Stage in Al-Aqsa University- Gaza
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The study aims to identify the effectiveness of employing microteaching in acquiring teaching skills of students teaching basic stage in Al-Aqsa University. The two researchers used the experimental method and a quota sample consisted of a group of (80) students who were distributed on the university two branches in Gaza and Khan younis and on males and females equally, and on four teaching courses counted (20) students for each. The study tool represented in an observation card ,and the results showed statistically significant differences between the level of all the skills of teaching and between the standard rate (75%) in favor of teaching skills, also showed statistically significant differences attributed to the variable of the univ

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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of The College Of Education For Women
Exploring the Effectiveness of two Scales for Measuring Cultural Intelligence of the Preparatory School Students
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The present study aims at exploring tow cultural intelligence scales of preparatory school students. It also aims at finding out the statistically significant differences according to gender and specification. Accordingly, the present study seeks to answer the following questions:

  1. Is there cultural intelligence of the preparatory school students?
  2. Is there any statistically significant differences according to gender and specification variables?
  3. Is there a scale more effective than cultural intelligence scales?

The stratified random sampling method is used to for selecting the sample of (216) students of scientific and humanistic specifications from

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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Science
Study the correlation between Human Chorionic Gonadotropin Hormone and Some Biochemical Parameters in Iraqi Women with Pregnancy-Induced Hypertension
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Publication Date
Tue Jul 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Classification and monitoring of autism using svm and vmcm
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Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Deep Learning of Diabetic Retinopathy Classification in Fundus Images
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Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

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Publication Date
Tue Aug 02 2022
Journal Name
Ijhs
The association between polymorphism of TCF7L2 gene rs12255372 G/T and type 2 diabetes mellitus in Iraqi women suffering from menopause
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Type 2 diabetes mellitus (T2DM) became the most prevalent health problem. Almost half of the world's people are ignorant that have diabetes. Menopause occurs as an important alteration in women through which take place the change in sex hormones, distribution in fat،s body, and metabolism, altogether which participate in the metabolism disease such as type 2 diabetes mellitus. Several studies have appeared the association between the TCF7L2 gene and different diseases like type 2 diabetes mellitus (T2DM). This study aimed to detect the relation of the genetic variation polymorphism for the TCF7L2 gene (rs12255372 G/T) in Iraqi women menopausal with T2DM. The outcomes indicated the increased levels of biochemical characteristics including H

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Incidence of Toxoplasmosis in Psoriasis Patients and Possible Correlation with Tumor Necrosis Factor-α
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            Toxoplasma gondii is an opportunistic parasite in immune-compromised persons. The prevalence of toxoplasmosis in psoriasis patients is investigated. In addition, the treatment effect on psoriasis patients infected with toxoplasmosis through evaluating Tumor Necrosis Factor-α (TNF-α) cytokine levels is studied. Blood samples were collected from 130 individuals who involved 60 control samples and 70 samples with psoriasis. They attended Medical City Hospital in Baghdad province from October 2017 - February 2018. Then, the anti- T. gondii antibodies (IgM and IgG) and TNF- α in the sera were determined via the enzyme linked immune-sorbent assay. The highe

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