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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
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Post-Traumatic Stress Disorder among Women with Breast Cancer in Iraq: A Preliminary Report
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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Inspecting Hybrid Data Mining Approaches in Decision Support Systems for Humanities Texts Criticism
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The majority of systems dealing with natural language processing (NLP) and artificial intelligence (AI) can assist in making automated and automatically-supported decisions. However, these systems may face challenges and difficulties or find it confusing to identify the required information (characterization) for eliciting a decision by extracting or summarizing relevant information from large text documents or colossal content.   When obtaining these documents online, for instance from social networking or social media, these sites undergo a remarkable increase in the textual content. The main objective of the present study is to conduct a survey and show the latest developments about the implementation of text-mining techniqu

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Publication Date
Sun Apr 04 2010
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Iraqi Breast Cancer: A Review on Patients' Demographic Characteristics and Clinico-Pathological Presentation.
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Background: Breast Cancer is the commonest type of malignancy in Iraq. The Iraqi Cancer Registry displays an obvious trend for the disease to affect younger women with advanced stages at the time of presentation. This report presents a review on the main demographic characteristics and clinicopathological parameters in Iraqi patients diagnosed with breast cancer.
Patients & Methods: The study was carried out on 721 out of a total of 5044 patients (14.3%) who complained of palpable breast lumps that were diagnosed as cancer. The procedure for tumor nuclear DNA Ploidy assessment was performed by means of Image Cytometry. Immuno-cytochemical and  histochemical assays were applied for the determination of

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Publication Date
Sat Nov 28 2020
Journal Name
Iraqi Journal Of Science
Using Affiliation Rules-based Data Mining Technique in Referral System
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Referral techniques are normally employed in internet business applications. Existing frameworks prescribe things to a particular client according to client inclinations and former high evaluations. Quite a number of methods, such as cooperative filtering and content-based methodologies, dominate the architectural design of referral frameworks. Many referral schemes are domain-specific and cannot be deployed in a general-purpose setting. This study proposes a two-dimensional (User × Item)-space multimode referral scheme, having an enormous client base but few articles on offer. Additionally, the design of the referral scheme is anchored on the  and  articles, as expressed by a particular client, and is a combination of affi

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Publication Date
Sun Oct 02 2016
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Molecular Classification of Iraqi Breast Cancer Patients and Its Correlation with Patients’ Profile
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Background: Breast cancer is a complex, multifaceted disease encompassing a great variety of entities that show considerable variation in clinical, morphological and molecular attributes.
Objective: The aim of this study to evaluate patients’ molecular profile (Estrogen receptor, Progesterone receptor, HER2/neu and Ki-67).
Patients & Methods: This is a cross-sectional descriptive study was done in Baghdad oncology teaching hospital from December 2015 to April 2016, carried on 100 breast cancer female patients with their age range from 27 to 73 years old and with their histopathology reports and (IHC) results.
Results: The highest incidence of breast cancer among patients in 5th (40-49 years) and 6th (50-59 years) decades o

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Publication Date
Mon Dec 25 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Knowledge, Attitudes and Barriers Towards Breast Cancer Health Education Among Iraqi Community Pharmacists
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With the increasing prevalence of breast cancer among female internationally, occupies about 25% of all cases of cancer, with a measured 1.57 million up to date cases in 2012. Breast cancer has turn a most warning to health of female in Iraq, where it is the major cause of death among women after cardiovascular diseases, with a mortality rate of 23% related cancer. Recently there is a crucial requirement to include community pharmacists in health elevation activities to support awareness and early diagnosis of cancer, specially breast cancer. The aim of this study is to assess knowledge, attitude and perceived barriers amongst Iraqi community pharmacists towards health promotion of breast cancer. This study is cross sectional research. A

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Publication Date
Sun Dec 01 2019
Journal Name
Computers And Electronics In Agriculture
Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
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Publication Date
Sun Sep 02 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Applying food frequency questionnaire to evaluate the dietary pattern and life style on women with breast cancer
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Background: Breast cancer is the most common cancer among women and ranked number two after
lung cancer in the world. According to the World Health Organization, breast cancer accounts for
22.9% among cancers in women in 2012.
Objective: This study was designed to evaluate the dietary pattern particularly dairy products
consumption and the role of lifestyle on women with breast cancer in Baghdad city and its suburbs.
Subjects and Methods: The study was conducted on 100 women with breast cancer, as a case group,
compared with a control group comprised of 100 healthy women. Demographic data were collected
from both groups. A food frequency questionnaire was used of 33 items of foods for reporting the

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Evaluation of Zinc, Copper, and Lead Levels in The Blood of Breast Cancer Women in Baghdad City
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     The current study was conducted on 100 females who were divided into two main groups; 60 with breast cancer and 40 healthy controls. Blood samples were collected from both premenopausal and postmenopausal breast cancer and healthy women. The samples were appropriately processed for the analysis of trace elements (zinc, copper, and lead) by using flame atomic absorption spectrophotometry (FAAS). The results showed a highly significant decrease (p< 0.01) in the mean serum level of zinc of in both pre- and postmenopausal breast cancer women (71.7 + 5.1 and 70.4 + 5.4 µg/dL, respectively) compared with healthy controls (89.7 + 10.2 and 97.5 + 13.2 µg/dL,  respectively) . Also, a highly significant

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Accounting Mining Data Using Neural Networks (Case study)
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Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a

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