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

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

We are, today, facing a torrent of information, ideas, images and videos due to advances of communication technology and electronic publishing. In addition to the proliferation of social networking sites that allow individuals to use them and participate in their channels without any restrictions limiting their freedom in publishing. Due to these sites many terms have emerged like alternative media which use internet and its various techniques to serve its objectives notably the freedom of expression without restrictions. This research studies the phenomenon of interactive media i.e. alternative media through Facebook along with the freedom that makes it spreading in the society and the relation of individual freedom with social diversit

The current study shows the cytotoxicity effect of the Crassula ovata n-hexane extract on esophagus can¬cer. C. ovata is a perennial succulent plant belonging to the Crassulaceae family. In Africa, the leaves were used medicinally to cure epilepsy and diarrhoea by boiling them in milk. The hexane fraction, which is obtained through the maceration method, demonstrates the presence of many compounds that have an anticancer effect, which are ob¬tained by gas chromatography - mass spectroscopy. The phytosterol compound was isolated by a preparative thin layer chromato¬graph and was identified by liquid chromatography - mass spectroscopy. The hexane fraction was found to possess a strong anticancer effect against esophagus cancer. The

Despite not being digested, trace elements and/or heavy metals are important for the activity of enzymes, physiological processes, and homeostasis. If certain trace elements are present in excess, they can have harmful effects and pose major health hazards. Objective: The aims to examine the connection between serum zinc, copper levels, and the Cu/Zn ratio, and several anthropometric parameters, including an index of body mass and the waist-hip ratio. In our study, we used atomic absorption spectrometry (AAS) to measure serum levels of copper (Cu) and zinc (Zn) in 60 individuals, 30 patients with kidney cancer and 30 healthy controls. We assessed serum uric acid, creatinine, and urea using the semi-auto analyzer BA-88A (Korea). The results

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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

In this study, we tackle the understudied area of Artificial Intelligence (AI) and its role in examining how modern revolutions may affect political systems across the Middle Eastern region. despite hundreds of studies documenting Middle Eastern uprisings over the past three decades, there has been little effort to harness AI to better understand or predict these multifaceted events. This study seeks to address this gap by assessing the performance of AI-intelligence in analyzing (broadly) revolutionary processes and their effects on regional political systems. The research uses a mixedmethod methodology that involves a systematic literature review of contemporary scholarly articles, and an analytics study using AI tools. Our results show t