Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we modified the Correlation Feature Selection (CFS) with Best First Search (BFS) established on the Discriminant Index (DI) so as to reduce the complexity of time and get high accuracy. Secondly, Bayesian Rough Set (BRS) classifier is applied to predict the breast cancer and help the inexperienced doctors to make decisions without need the direct discussion with the specialist doctors. The result of experiments showed the proposed system give high accuracy with less time of predication the disease.
The importance of topology as a tool in preference theory is what motivates this study in which we characterize topologies generating by digraphs. In this paper, we generalized the notions of rough set concepts using two topological structures generated by out (resp. in)-degree sets of vertices on general digraph. New types of topological rough sets are initiated and studied using new types of topological sets. Some properties of topological rough approximations are studied by many propositions.
Background: although breast cancer in young women is less common and often overlooked, it is still considered a major health concern.
Objectives: to evaluate the demographic, clinical, radiological and histopathological characteristics of breast cancer among a sample of Iraqi women diagnosed under the age of 40 years.
Patients and methods: a retrospective study enrolled 73 females below the age of 40 years with a history of breast cancer. All data was extracted from an established information system database designed by the Principal Investigator of the Iraqi National Breast Cancer Research Project under supervision of the International Agency for Research on Cancer (IARC) over a 4-years period from 2011 to 2014.
Results: sevent
Background: although breast cancer in young women is less common and often overlooked, it is still considered a major health concern.
Objectives: to evaluate the demographic, clinical, radiological and histopathological characteristics of breast cancer among a sample of Iraqi women diagnosed under the age of 40 years.
Patients and methods: a retrospective study enrolled 73 females below the age of 40 years with a history of breast cancer. All data was extracted from an established information system database designed by the Principal Investigator of the Iraqi National Breast Cancer Research Project under supervision of the International Agency for Research on Cancer (IARC) over a 4-years period from 2011 to
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Background : Breast cancer is the most common cancer of
women. When breast cancer is detected and treated early,
the chances for survival are better. Surgery is the most
important treatment for non-metastatic breast cancer.
Al-Kindy Col Med J 2008 Vol.5(1) 40 Original Article
Objectives : The aim of this study is to review different
clinical presentation and to evaluate types of surgical
procedures and complications in treatment of nonmetastatic breast cancer.
Method : During the period from Jun 1998 to May 2005,
93 patients with non-metastatic breast cancer were
diagnosed and treated surgically in 2 hospitals in Baghdad (
Hammad Shihab military hospital and Al-Kindy teaching
hospital).
Results : Wo
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
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Background & Objective: Breast cancer (BC) is the most prevalent disease among women around the world, considered the world's leading cause of death (15% of the total cancer deaths) in women in 2018. β-catenin is a multifunctional protein located in the cytoplasm and/or nucleus of the cell. Several studies suggested that β-catenin expression plays a critical role in cancer invasion and metastasis. This research sought to examine β-catenin expression in breast cancer and its associations with clinico-pathological features (such as histopathological types, grade, and invasion depth of tumor as well as lymph node involvement) and breast cancer patient survival. Methods:
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Background: Breast cancer composed of several biologic subtypes that have response to hormonal therapy. Tamoxifen is hormonal therapy with tissue- pecific antagonistic or agonist effects, the latter being responsible for multiple effects on lipid metabolism in women .
Objective: This study was designed to determine the impact of Tamoxifen on the serum lipid profile in breast cancer women.
Patients and methods: Prospective observation cohort study conducted at Oncology Teaching Hospital, Medical city complx.starting from October 2015 to October 2016. A total number of 40 premenopausal women with breast cancer were enrolled in this
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Background: Epstein Barr Virus (EBV) infection has been implicated in pathogenesis of several types of carcinomas such as nasopharyngeal carcinoma, gastric cancer and bladder cancer and has recently been associated with breast cancer.
Objective: To evaluate the relations between Epstein Barr virus-encoded small RNA (EBER) and breast cancer.
Methods: Twenty two cases of breast cancer were retrieved from the Al-Kadhimiya Teaching Hospital in Baghdad. Clinical data were analyzed from the medical records and formalin fixed, paraffin embedded tumor tissue were examined by Chromogeneic in situ hybridization (ISH) technique for the detection of EBER.
Results: The expression of EBER in tissues patients with breast cancer in the present
Presupposition in Fitzgerald the Rough Crossing
The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
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