Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accu

Background : To assess the actual practice of breast self-examination (BSE), as an early detection tool for breast cancer, among a sample of patients affected with breast cancer in Iraq.Methods: A random sample of 200 female patients with breast cancer was analyzed to evaluate the extent of their actual practice of breast self-examination before the diagnosis of the disease.  The examined variables included the age of the patients, marital status, education, occupation, smoking habit, family history of cancer, frequency of gravidity, parity and abortions. Results: The age of patients ranged from (24-70) years with a mean age of 48 years. The highest frequency of the examined sample

Breast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

Urokinase plasminogen activator (uPA), urokinase plasminogen activator receptor (uPAR) and plasminogen activator inhibitor-1(PAI-1) are essential for metastasis, and overexpression of these molecules is strongly correlated with poor prognosis in a variety of malignant tumors. This study revealed direct correlation between immunohistochemical expression of uPA with pathological stage. No significant association of immunohistochemical expressions of uPA, uPAR and PAI-1 with immunohistochemical expressions for estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor -2 (HER-2/neu), and direct association between immunohistochemical expressions of (uPA and uPAR) as well as between immunohistochemical expr

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

Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

This study focused on the expression and regulation of BRCA1 in breast cancer cell lines compared to normal breast. BRCA1 transcript levels were assessed by real time quantitative polymerase chain reaction (RT-qPCR) in the cancer cell lines. Our data show overexpression of BRCA1 mRNA level in all the studied breast cancer cell lines: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 along with Jurkat, leukemia T-lymphocyte, the positive control, relative to normal breast tissue. To investigate whether a positive or negative correlation exists between BRCA1 and the transcription factor E2F6, three different si-RNA specific for E2F6 were used to transfect the normal and cancerous breast cell lines. Interestingly, strong negative relationship was found b

Background: The role of cytokines in cancer immunity and carcinogenesis in general has been well established, which play an important role in the pathogenesis of many solid cancers.This study aimed to estimate serum levels of IL-2 and IL-4, and to shed light on the correlation of these interleukins with progression of breast cancer.
Patients and Methods: The study included 80 women, it comprised of 45 breast cancer patients, 12 patients with benign breast lesions and 23 apparently healthy controls. ELISA method has been used for estimation the level of IL-2 and IL-4 in serum of three studied groups.
Results: This study showed elevation of IL-4 level in the sera of breast cancer patients with significant dif

Background: management modalities for liver metastasis from primary breast cancer are evolving steadily but systemic chemotherapy remains the mainstay of treatment.
Patients and methods: 30 patients with breast carcinoma and liver metastasis managed at (Baghdad teaching hospital) during the period from Jan. 2005 to Jan. 2007.
Results: 16 patients showed response to chemotherapy. 20% complete response was found and 33% showed partial response 57% went into progressive disease. The duration of response lasted for less than six months in 4 patients and more than six months in two patients.
Conclusion: chemotherapy remains the mainstay of treatment of liver metastasis but new modalities of treatment add much