Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc

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

Many previous investigations have found quercetin to be a powerful antioxidant and antitumor flavonoid, but its poor bioavailability has limited its use. This current study investigated the effects of two newly synthesized Quercetin Schiff bases containing 2-amino thiadiazole-5-thiol (Q1), and its benzyl derivatives (Q2) on MCF-7 human breast cancer cells. Cell viability and apoptosis were assessed to determine the toxic effects of Q1 and Q2. Cytotoxicity valuation showed that both compounds inhibited MCF-7 cell growth, and lactate dehydrogenase (LDH) activity increased in a dose-dependent aspect compared to the control group. Comet assay results observed that Q1 and Q2 induce more serious DNA damage than the control (untreated cell

Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

Objective: In order to evaluate the effect of different typed of Separating Medium on the roughness of the fitted
tissue surface of acrylic denture base.
Methodology: Chosen three types of separating medium (Group A Tin foil), (Group B Detery Isolant),(Group C
Cold Mould Seal),used 30 samples of hot cure acrylic resin ,10 samples for each group, after complete curing of
these samples , Profilometer device was used to measure the surface roughness of each sample in all groups.
Results: Using One Way ANOVA Test and LSD test, the results were highly significant in differences among all
groups. Although (Group A) showing lest roughness, (Group B) showing a satisfactory result of roughness, While
(Group C) Showing the hig

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

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate