Breast cancer is the commonest cancer affecting women worldwide. Different studies have dealt with the etiological factors of that cancer aiming to find a way for early diagnosis and satisfactory therapy. The present study clarified the relationship between genetic polymorphisms of BRCA1 & BRCA2 genes and some etiological risk factors among breast cancer patients in Iraq. This investigation was carried out on 25 patients (all were females) who were diagnosed as breast cancer patients attended AL-Kadhemya Teaching Hospital in Baghdad and 10 apparently healthy women were used as a control, all women (patients and control) aged above 40 years. The Wizard Promega kit was used for DNA isolation from breast patients and normal individuals. B

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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

 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

This study evaluated the knowledge and practice of breast self-examination (BSE), among a sample of educated Iraqi women. The study sample comprised 858 women aged 18–62 years affiliated to 6 major Iraqi universities, categorized according to occupation as teaching staff (11.5%), administrative staff (18.0%) and students (70.5%). Data were collected by a self-completed questionnaire. In all, 93.9% of the women had heard about BSE, the main source of information was television (39.9%), doctors (18.4%) and the awareness campaign of the Iraqi National Breast Cancer Research Programme (11.6%). Only 53.9% of the women practised BSE; the most common excuses by those that did not were lack of knowledge of the significance of BSE (42.0%) and lack

Objective: The study aims at assessing the food frequency intake and dietary habits for diabetic pregnant
women.
Methodology: A descriptive study is carried out for the period from November4th 2013 to August
25th 2014. A purposive "non-probability" sample of one hundred diabetic pregnant women is selected from
the Diabetic and Endocrine Center in Al-Amarha City. A questionnaire is developed as a tool of data
collection. Content validity of the study instrument is determined through panel of experts. Split-half
reliability technique is used for reliability determination of the study instrument which depicts a reliability
coefficient of (0.79) for the entire scale. A structured interview with each diabetic pregnant wom

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Background: Breast cancer is the commonest type of malignancy worldwide and in Iraq. It is a serious disease that affects the general health and cause systemic changes that affect the physical and chemical properties of saliva leading to adverse effects on oral health. This study was conducted toassess the tumor marker CA15-3 and selected elements in saliva and their relation to oral health status among breast cancer patients compared to control group. Materials and Methods: The total sample consisted of 60 women aged 35-45 years. 30 women were newly diagnosed with breast cancer before taking any treatment and surgery (study group) and 30 women without clinical signs and symptoms of breast cancer as a control group. Dental caries was record

Breast mass is by far the most important clinical problem that concerns the breast today. This study was carried out to evaluate diode laser as a cutting tool in breast mass excision and as a hemostatic tool for coagulation during surgery. Using 810 nm diode laser with optical fiber 600μm in diameter of conical tip, udder (cow's breast) tissue, and three female patients (mean age of 35.5 y with clinically palpable breast mass) had been used in this study. The patients were followed up regularly postoperatively. In preliminary work on udder tissue, the power needed for cutting and excision was 15W (power density= 5.3 kW/cm2). The time consumed for excision of a piece of udder tissue, 40×10×3 mm in dimensions was 5 min. The depth range