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Breast Cancer Decisive Parameters for Iraqi Women via Data Mining Techniques
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Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using a training data rather than cross validation. The decision tree algorithm J48 is applied to detect and generate the pattern of attributes, which have the real effect on the class value. Furthermore, the experiments are performed with three machine learning algorithms J48 decision tree, simple logistic, and multilayer perceptron using 10-folds cross validation as a test option, and the percentage of correctly classified instances as a measure to determine the best one from them. As well as, this investigation used the iteration control to check the accuracy gained from the three mentioned above algorithms. Hence, it explores whether the error ratio is decreasing after several iterations of algorithm execution or not. Conclusion It is noticed that the error ratio of classified instances are decreasing after 5-10 iterations, exactly in the case of multilayer perceptron algorithm rather than simple logistic, and decision tree algorithms. This study realized that the TPS_pre is the most common effective attribute among three main classes of examined dataset. This attribute highly indicates the BC inflammation.

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Publication Date
Wed Apr 01 2009
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The Possible Cytoprotective Effects of Antioxidant Drugs (Vitamin E and C) Against the Toxicity of Doxorubicin in Breast Cancer Patients
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Background: Breast cancer is the culmination of a multi-step process that occurs over a period of several years or decades and as a cause of death, is a salient "free radical" disease. Aim: The present study aims on investigating the possible protective role of antioxidant drugs (vitamins E and C) to cardiac cells against the oxidative stress induced damage during doxorubicin chemotherapy in patients with breast cancer.
Patients and methods: Thirty two patients with different stages of breast carcinoma attending to Baghdad Teaching Hospital and ten healthy control subjects with age range between (29-61) years, mean (43.6±1.37) were included in this study. The patients were randomized into 3 groups, they

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Publication Date
Sun Jan 04 2015
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Dense breast as a risk factor in breast malignancy
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Background: One of the strongest risk factors for breast cancer is high breast density, relatively little fat in the breast and more connective and glandular tissue.
Objectives: this study aims to measure risk of increase breast density in correlation of CA breast & compare our results with results in other population, to compare the performance of ultrasonography and mammography in measuring breast density according to BIRDS system
Materials &methods: The study included 45 females .Measuring risk of increase breast density in correlation of CA breast & comparing the performance of ultrasonography and mammography in measuring breast density according to BIRADS system.
Results : there is stron

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Processing and interpretation of 3D seismic data of an oil field in central of Iraq using AVO techniques
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In this research, a qualitative seismic processing and interpretation is made up
through using 3D-seismic reflection data of East-Baghdad oil field in the central part
of Iraq. We used the new technique, this technique is used for the direct hydrocarbons
indicators (DHI) called Amplitude Versus Offset or Angle (AVO or AVA) technique.
For this purposes a cube of 3D seismic data (Pre-stack) was chosen in addition to the
available data of wells Z-2 and Z-24. These data were processed and interpreted by
utilizing the programs of the HRS-9* software where we have studied and analyzed
the AVO within Zubair Formation. Many AVO processing operations were carried
out which include AVO processing (Pre-conditioning for gathe

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Development of a Job Applicants E-government System Based on Web Mining Classification Methods
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     Governmental establishments are maintaining historical data for job applicants for future analysis of predication, improvement of benefits, profits, and development of organizations and institutions. In e-government, a decision can be made about job seekers after mining in their information that will lead to a beneficial insight. This paper proposes the development and implementation of an applicant's appropriate job prediction system to suit his or her skills using web content classification algorithms (Logit Boost, j48, PART, Hoeffding Tree, Naive Bayes). Furthermore, the results of the classification algorithms are compared based on data sets called "job classification data" sets. Experimental results indicate

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Publication Date
Thu Oct 01 2020
Journal Name
Defence Technology
A novel facial emotion recognition scheme based on graph mining
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Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

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Publication Date
Wed Feb 20 2019
Journal Name
Iraqi Journal Of Physics
Assessment of nuclear radiation pollution in uranium mining-impacted soil
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Activities associated with mining of uranium have generated significant quantities of waste materials containing uranium and other toxic metals. A qualitative and quantitative study was performed to assess the situation of nuclear pollution resulting from waste of drilling and exploration left on the surface layer of soil surrounding the abandoned uranium mine hole located in the southern of Najaf province in Iraq state. To measure the specific activity, twenty five surface soil samples were collected, prepared and analyzed by using gamma- ray spectrometer based on high counting efficiency NaI(Tl) scintillation detector. The results showed that the specific activities in Bq/kg are 37.31 to 1112.47 with mean of 268.16, 0.28 to 18.57 with

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Publication Date
Tue Jul 18 2023
Journal Name
Journal Of Current Researches On Social Sciences
A Study on Sociocultural Features among Turkish and Iraqi Women
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SM ADAI, BN RASHID, Journal of Current Researches on Social Sciences, 2023

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Publication Date
Mon Jan 30 2023
Journal Name
Iraqi Journal Of Science
Histological Estimation of Ovaries Cystic Lesions in Iraqi Patients’ Women
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      Ovarian cystic lesions are one of the most common pathologic disorders in gynecology and a common reason for surgery. The purpose of the study was to determine the histopathologic characteristics of benign cystic ovarian lesions and their correlation to age, type, laterality, locularity, and size of ovarian cystic lesions. This is a retrospective study carried out on 100 cases from the archive in the Imam Kadhimian medical city and the educational laboratories of Baghdad medical city, out of 100 patients, the most common age group that underwent cystectomy was 20-40 years old. The vast majority of the cysts were non-neoplastic (67%) while the neoplastic cysts occupy 33% of all cysts. The most common non-neoplastic cyst was cor

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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Risk Factors influencing Post-Partum Depression Severity in Iraqi Women
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Background: Post-partum depression (PPD) is a form of postnatal depression that affects mothers. Clinical manifestations usually appear within six months after delivery. Risk factors that influence the severity of post-partum depression are not fully known in the Iraqi population.
Objectives: We aim to evaluate the risk factors and identify potential predictors that may influence the symptom levels (severity) of post-partum depression among Iraqi women from Baghdad.
Subjects and Methods: The current study is cross-sectional, and we used the Edinburgh Postnatal Depression Scale (EPDS) and a cut-off value of 13 to differentiate patients into two those with lower symptom levels (LSL) and higher symptom levels (HSL). We also explored p

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