Background: Although mammography is a powerful screening tool in detection of early breast cancer, it is imperfect, particularly for women with dense breast, which have a higher risk to develop cancer and decrease the sensitivity of mammogram, Automated breast ultrasound is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound, this study aims to evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with handheld ultrasound in the detection and characterization of breast lesions in women with dense breasts. Objectives: To evaluate the diagnostic efficacy of Automated breast ultrasound and compare

Background: Breast lump is one of the most common prevalent complaint of patients attending breast clinics.

Objective: To determine if there is any change in the pattern of common breast, diseases presenting as breast lumps between pregnant and non-pregnant women among patients attending Al-Elwiya Breast Clinic.

Methods: This is a cross – sectional study, with convent's patient sampling setting in AL-Elwiya Breast Cancer Early Detection Clinic from 1^st Feb. to 1^st May 2018, we collected data from patients with breast lumps including the age groups, pregnancy status, parity status, previous breast diseases, hormonal drugs, menstrual cycle, breast fe

Two series of 1,3,4-oxadiazole derivatives at the sixth position of the 2,4-di-tert-butylphenol group were synthesized.

Feature selection algorithms play a big role in machine learning applications. There are several feature selection strategies based on metaheuristic algorithms. In this paper a feature selection strategy based on Modified Artificial Immune System (MAIS) has been proposed. The proposed algorithm exploits the advantages of Artificial Immune System AIS to increase the performance and randomization of features. The experimental results based on NSL-KDD dataset, have showed increasing in performance of accuracy compared with other feature selection algorithms (best first search, correlation and information gain).

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

. Mesopotamian art is thase mployed all around him into forms for artistic purposes and different con not at ions help him to understand the world around him and customized for their interests

The mural architectural art has distinguished traits that made it promote to the rank of the prominent arts that have been employed  by the Mesopotamian human to relate to the world  the heroic deeds and exploits  of that civilization ,that formed greatest and most splendid wonderful works that still illustrious and outstanding  till nowadays .The mural  architectural  art of pottery and glazed considered one of the most ancient wonders  of Mesopotamian creation in Old Iraq .The best quintessence of mural

This study aims to identfy virtual plastic art exhibitions in light of the challenges of the Corona pandemic. It used a descriptive analytical method through several questions and examining future challenges via the Internet in publishing virtual plastic art exhibitions in many parts of the world in light of the challenges of the Corona pandemic. For that, it used Arab and foreign references.
The study reached many results, the most important of which are: The detection of virtual reality applications and their impact on the plastic arts exhibitions sector. Besides, the insights gained from future art gallery research with VR technology could provide direct and practical value for this sector. By using a technology, similar to the “

The research (The Aesthetics of Lumia Art in Contemporary Textile Arts: An Analytical Study) included four chapters, the first to explain the research problem summarized by the question: Does the art of Lumia achieve aesthetic values in contemporary textile arts?, and aims to: Identify the aesthetics of Lumia art and its applied uses in contemporary textile arts, within the time period (2013-2022). The third chapter included: research procedures and sample analysis (4) models according to the descriptive analytical approach, and the fourth chapter dealt with: results, conclusions and recommendations as well as sources.

The research aims to monitor and analyze the visual and symbolic features, derived from the Omani heritage, and inspired by the concept of local identity, for a selection of contemporary Omani graphic art works, which represent a mixed, multi-category of research sample, comprising three levels: the works of professional Omani artists, and the works of young artists and specialized students, as well as the work of a number of active academics in the field of graphic theorizing and teaching. The sample is also divided - in terms of technical classification - into a category of works executed using traditional engraving and printing media, and a category of works executed using modern and digital graphic printing media.
Through the da