To achieve the objectives of the study, a non –probability (purposive) sample of (50) nurses were selected those were working at the oncology wards at the above listed hospitals. The data selected according to the criteria of the study sample. The validity of the questionnaire was determined through an expert panel consists of (11) specialist expert and its reliability was determined through a pilot study by test – retest which was estimated as averages (R=0.89). Data was collected by direct interview technique using the questionnaire formal and data was analyzed by application of descriptive & inferential statistical methods (frequency, percentage, mean of score and Chi-Square). The resul

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Background: Understanding the challenges facing nurses toward providing care to patients with cerebrovascular accidents is the initial step in developing strategies to address these challenges, thereby ensuring high-quality care. Aim: The study aimed to assess the challenges experienced by nurses in delivering care to patients with CVAs in neurological wards. Results: Of the 80 questionnaire participants in the qualitative part, (MS = 0.66) reported a "moderate" rating as an overall assessment. These challenges are divided into workload (MS = 0.53) at a moderate rate, the psychological burden (MS = 0.85) at a high rate, the supporting materials (MS = 0.85) at a high rate, the sense of responsibility (MS = 0.77) at a high rate, and the role

Background: The rapid integration of Artificial Intelligence (AI) into healthcare necessitates that nursing education evolves to equip students with essential technological competencies. Objectives: To explore pediatric nursing students' perceptions of AI in nursing and analyze associations with sociodemographic factors and prior AI knowledge. Methods: A descriptive cross-sectional study was conducted from December 2024 to March 2025 across five universities in Baghdad. A non-probability sample of 500 pediatric nursing students completed the Shinners Artificial Intelligence Perception (SAIP) tool. Data were analyzed using descriptive statistics and inferential comparisons (t-tests/ANOVA) via SPSS. Results: Participants had a mean ag

Objective: This study aims to assess the level of nurse's knowledge regarding toxoplasmosis management
in pregnant women.
Methodology: A descriptive analytic study was carried out from January 2012 to March 2012. A sample of
(70)nurses who provide prenatal care to pregnant women at primary health care centers of AL-Adala,ALHindia,AL-Askary,AL-Jamea,AL-Ansar
and AL-Salam in AL-Najaf city. The questionnaire was self-completed
and included questions on sociodemographic characteristics and toxoplasmosis aspects.
Results: The findings of the study indicated that (44.3%) of nurses have moderate level of knowledge.
(32.9%) of nurses was with age ranging from 31-36 years. (74.3%) were male. (52.9%) were secondary
graduate

Objective(s): To evaluate nurses' knowledge toward pain management of leukemic child in oncology wards
how were receiving chemotherapy.
Methodology: A descriptive study was conducted in two hospitals on (40) nurses, who provided care for the
children with leukemia in oncology wards (2) hospitals (Children Welfare Teaching Hospital and Child’s Central
Teaching Hospital) in Baghdad city from October 2010 up to the 27th of October 2011 for the purpose of
evaluating their knowledge towards pain management for leukemic child. A purposive "non-probability
sample" was selected that consisted of (40) nurse who are working in oncology wards. A questionnaire format
was used which consist of (2) parts, the first part includes

Objectives : The study aims to assessing nurses’ knowledge concerning peritonitis- dialysis association at the
peritoneal dialysis units, and to identifying the relationship between some nurses’ knowledge and some of their
demographic characteristic.
Methodology : A descriptive study was carried out at the peritoneal dialysis units in Baghdad Teaching
Hospitals started from November 29th 2004 to August 15th, 2005. A purposive sample of (52) nurses was
selected from Baghdad Teaching Hospitals. The data were collected through the use of constructed
questionnaire, which comprised of (97) items as an interview questionnaire technique as mean of data
collection. The reliability of the instrument was determined through

      Abstract:

Objective: The study was done to evaluate nurses’ knowledge and practices toward physical restraint at critical care unit

Methodology: Fifty nurses, who were selected by a non-probability (convenient) sampling method, participated in this descriptive study. The instrument of the study was knowledge parts of the questionnaire were initially developed in the U.S.A for nursing homes; in 2006 they were adopted for all hospital units by the original developers. The knowledge section of the questionnaire consisted of 20 items, which were used to measure knowledge of nurses towards the definition, indications and contra