Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

Objective: The study aims to determine the effectiveness of the continuing nursing education
program on nursing staffs knowledge in kidney transplantation unit and to find out the relationship
between nursing staffs knowledge and demographic characteristics (age, gender, education level, and
years of experiences in kidney transplantation unit).
Methodology: A quasiexperemental design (One-group Pretest - Posttest design) was carried out in
kidney transplantation units at Baghdad Teaching Hospitals, from December 2011 to July 2012. A nonprobability
(purposive sample) of (16) nurses were selected from kidney transplant units at Baghdad
teaching hospitals, the choice was based on the study criteria. The data were collec

Behavioral and emotional disorders represent one of the commonest problems facing children in particular and disturbing their parents and educators in general. This is because Iraqi people have long been living in difficult conditions and faced various terrorists’ operations, such as killing, destruction, robbery, and looting. Such operations are said to be one of the reasons that leads to the development of such disorders, and may negatively affect the psyche of the child and be reflected on his behavior as represented by playing with the IPad for hours, and suffering from nightmares. Accordingly, the current research aims to examine specifically the commonest negative behavioral disorders among kindergarten children during the post-t

IRA Dawood, JOURNAL OF SPORT SCIENCES, 2016 - Cited by 3

The Coronavirus Disease 2019 (COVID-19) pandemic has caused an unprecedented disruption in medical education and healthcare systems worldwide. The disease can cause life-threatening conditions and it presents challenges for medical education, as instructors must deliver lectures safely, while ensuring the integrity and continuity of the medical education process. It is therefore important to assess the usability of online learning methods, and to determine their feasibility and adequacy for medical students. We aimed to provide an overview of the situation experienced by medical students during the COVID-19 pandemic, and to determine the knowledge, attitudes, and practices of medical students regarding electronic medical education.

Introduction and Aims: Job burnout such as occupational hazards that have been considered in recent years. This research aimed to investigate the relationship between religious beliefs and job burnout among nurses working in hospitals in Gonabad city in 2017. Materials and Methods: This study is cross-sectional and correlational study. The sample consisted of 100 nurses in Gonabad city who were selected using stratified randomized method. Using the Maslach job burnout and Alport religious beliefs Inventories, data were collected and were analyzed with SPSS version 16 and Pearson, Spearman and independent sample T tests were analyzed. Significant level was considered less than 0.05. Results: Average job burnout in nurses working in hospit

Education is the most powerful and important weapon in fighting poverty and unemployment because it provides students with new skills that appropriate the new market requirements and fair distribution of natural resources. It also transfers knowledge, skills, and ethics over generations. Education aims to create effective leaders who go under training and rehabilitation process, create a new human and instill faith, generate the creativity and innovation, and keep abreast with scientific process, updating curriculum, and finally, applying the technical education

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat