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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
Thu Jan 01 2026
Journal Name
Desalination And Water Treatment
Microplastics toxicity: Classification, sources, exposure routes, and experiments
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Microplastics (MPs), including polymers such as polyethylene, polyvinyl chloride (PVC), and polystyrene (PS), are widespread environmental contaminants detected in air, water, soil, and food. These particles originate from the breakdown of larger plastics and from direct industrial and consumer sources, including packaging, textiles, and personal care products. MPs enter the human body primarily through ingestion, inhalation, and dermal contact, with food, water, and air serving as major exposure pathways. Once internalized, MPs have been found in various human tissues and biological fluids, indicating their capacity for bioaccumulation. Toxicological studies in experimental models and occupational settings link MP exposure to oxidative str

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Publication Date
Sat Jan 01 2022
Journal Name
Intelligent Automation & Soft Computing
A Novel Classification Method with Cubic Spline Interpolation
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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Wed Jan 01 2025
Journal Name
Karbala Magazine Of Physical Edu. Sciences
تأثير استخدام أدوات وجهاز المرونة المساعد في بعض القدرات الحركية وتعليم مهارة القوس الخلفي على جهاز عارضة التوازن في الجمناستك الفني للنساء.
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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Building social intelligence scale and applied to a sample at the Deprived and non-Deprived students from their parents at the Secondary stage
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The current research aims to :
•know the level of social intelligence of the sample as a whole .
. •taraf statistically significant differences in social intelligence between disadvantaged and
non-disadvantaged peers .
To achieve these objectives, the selected sample of Talbhalmrahlh medium and specifically
students of the second grade average, were chosen randomly stratified's (360) students
included sex (male, female) and (deprived of the Father and the non-deprived) for the
academic year (2013-2014) for the province of Baghdad on both sides (Rusafa-Karkh (
As applied to them measurements of social intelligence, which is prepared by the researcher,
having achieved _khasaúsma of psychometric (valid and re

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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science &amp; Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between some of linear classification models with practical application
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Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

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Publication Date
Fri Oct 02 2020
Journal Name
Biochem. Cell. Arch.
MORPHOLOGICAL DESCRIPTION AND COMPARATIVE HISTOLOGICAL STUDY OF THE LIVER IN TWO IRAQI MAMMALS : WEASEL (HERPESTES JAVANICUS) AND EASTERN GRAY SQUIRREL (SCIURUS CAROLINENSIS
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The results of the current study showed that the liver of H. javanicus appeared as large lobulated organ divided into six distinct lobes, that filled the cranial region and little extended to the middle region of abdominal cavity. On the other hand, liver of S. carolinensis laid against the diaphragm, occupied the cranial region of the abdominal cavity and consisted of five lobes. The liver is surrounded with a thin capsule of dense regular collagenous connective tissue and few numbers of smooth muscles fibers can be seen in the capsule that covered the squirrel liver. The liver parenchyma divided into a large number of interconnected hepatic lobules marked only by the abundant amount of connective tissue bordered the triads, and within the

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Publication Date
Mon Oct 21 2019
Journal Name
Biochemical And Cellular Archive
MORPHOLOGICAL DESCRIPTION AND COMPARATIVE HISTOLOGICAL STUDY OF THE LIVER IN TWO IRAQI MAMMALS : WEASEL (HERPESTES JAVANICUS) AND EASTERN GRAY SQUIRREL (SCIURUS CAROLINENSIS)
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(Received 21 May 2019, Revised 30 September 2019, Accepted 21 October 2019)ABSTRACT : The results of the current study showed that the liver of H. javanicus appeared as large lobulated organ dividedinto six distinct lobes, that filled the cranial region and little extended to the middle region of abdominal cavity. On the otherhand, liver of S. carolinensis laid against the diaphragm, occupied the cranial region of the abdominal cavity and consisted of fivelobes. The liver is surrounded with a thin capsule of dense regular collagenous connective tissue and few numbers of smoothmuscles fibers can be seen in the capsule that covered the squirrel liver. The liver parenchyma divided into a large number ofinterconnected hepatic lobules marked

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