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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
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
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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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ELECTROCHEMICAL PREPARATION OF A MOLECULAR IMPRINTED POLYMER ELECTRODE FOR ESTEMATION OF ASPIRIN USING TWO DIFFERENT FUNCTIONAL MONOMERS.: ELECTROCHEMICAL PREPARATION OF A MOLECULAR IMPRINTED POLYMER ELECTRODE FOR ESTEMATION OF ASPIRIN USING TWO DIFFERENT FUNCTIONAL MONOMERS.
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For aspirin estimated, a molecularly imprinted polymer MIP-ASP electrodes were generated by electro-polymerization process, the electrodes were prepared by combining the template (aspirin) with (vinyl acetate (VA), 1-vinylimidizole (VIZ) as a functional monomer and N, N-methylene bisacrylamide (MBAA) as crosslinkers using benzoyl peroxide (BPO) as an initiator. The efficiency of the membrane electrodes was analyzed by differential pulse voltammetry (DPV). Four electrodes were synthesized using two different plasticizers, di-butyl sebacate (DBS), di-octyl phthalate (DOP) in PVC matrix. Scanning electron microscopy (SEM) was used to describe the generated MIP, studying the electrodes properties, the slope, detection limit, and life

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Publication Date
Sat Sep 30 2017
Journal Name
College Of Islamic Sciences
Authorization of women in divorce
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The Shari'a of Islam is the end of the laws revealed by God, including the goodness of the servants in the pension and the restored. They are supported by the enemies of Islam, especially in these days when the Islamic Ummah is subjected to a fierce campaign by its enemy to repel it from its religion through what they claim from the rights of women, including the right to equality with men.
      Islam came to announce to all mankind that women are part of life in society without which they can not imagine life for them. Islam did not leave women under the absolute authority of men, but raised their status and worked to liberate them, and these rights are divorced from her husband, does she have the right

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Publication Date
Thu Mar 30 2023
Journal Name
College Of Islamic Sciences
Human Dignity and the Problem of Women Cutting Off Prayer: Women Cutting Off Prayer
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Our creator has honored human beings and granted them a noble place, the provisions of the Islamic system are designed to strengthen and consolidate this dignity and respect. Since women are human beings, they have their respect, status and dignity. There are some prophetic sayings concerning women that may be understood as contrary to this value, the value of dignity and respect for human beings. One example is the Hadith of a woman cutting off a man’s prayer if she passed in front of his prayer. The study examines this topic and presents answers for it.

 

In dealing with the subject, the study followed the descriptive, analytical and deductive approach of mentioning legislative texts, analyzing them and deducing

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
TWO-PARAMETER GAMMA DISTRIBUTION AND LOG NORMAL DISTRIBUTION FOR DERIVATION OF SYNTHETIC UNIT HYDROGRAPH
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Most available methods for unit hydrographs (SUH) derivation involve manual, subjective fitting of
a hydrograph through a few data points. The use of probability distributions for the derivation of synthetic
hydrographs had received much attention because of its similarity with unit hydrograph properties. In this
paper, the use of two flexible probability distributions is presented. For each distribution the unknown
parameters were derived in terms of the time to peak(tp), and the peak discharge(Qp). A simple Matlab
program is prepared for calculating these parameters and their validity was checked using comparison
with field data. Application to field data shows that the gamma and lognormal distributions had fit well.<

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Diversity and Geographical Distribution of Sand Flies Phlebotomus papatasi (Diptera: Phlebotominae) by using Geometric Morphometric Technique from two Iraqi Provinces
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            The variation in wing morphological features was investigated using geometric morphometric technique of the Sand Fly from two Iraqi provinces Babylon and Diyala . We distributed eleven landmarks on the wings of Sand Fly species. By using the centroid size and shape together, all species were clearly distinguished.  It is clear from these results that the wing analysis is an essential method for future geometric morphometry studies to distinguish the species of Sand Flies in Iraq.

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