Ultrasound is a mechanical energy which can generate altering zones of compression and rarefaction along its path in the tissues. Ultrasound imaging can provide a real time screening for blood and multiple organs to aiding the diagnostic and treatment. However, ultrasound has the potential to deposit energy in the blood and tissues causing bio effects which is depending on ultrasound characteristics that including frequency and the amount of intensity. These bio effects include either a stable cavitation presented non thermal effects or inertial cavitation of harmful effect on the tissues. The non-thermal cavitation can add features in diagnostic imaging and treatment more than the inertial cavitation. Ultrasound Contrast agents are a micro

In this paper, we introduce the notions of Complete Pseudo Ideal, K-pseudo Ideal, Complete K-pseudo Ideal in pseudo Q-algebra. Also, we give some theorems and relationships among them are debated.

Background: Tumor associated tissue eosinophilia (TATE) has been described in a variety of neoplasms. In regard to squamous cell carcinoma, some studies worldwide done to assess stromal eosinophilia in oral and cervical squamous cell carcinoma. The objectives of this study is to evaluate the association of stromal eosinophilic infiltration of cutaneous squamous cell carcinoma and to detect the significance of this association.

Aim of the study

The aim of our study is to establish the relationship between the degree of stromal eosinophilia and the level of invasion and the histological grade in cutaneous squamous cell carcinoma.

Methods: In this retrospective study

Objective: To determine the prevalence of bullying among primary schools’ children with some associated factors, and resultant effects. Methodology: This cross-sectional study with analytic elements was carried out from February through April 2022. It included a sample of 410 students from six governmental primary schools from both sides of Baghdad city. A self-constructed questionnaire was used. It comprised the following parts: Part (1): socio-demographic data, Part (2): questions that review the students’ exposure to bullying, and Part (3) entails the effects of bullying on those children. Results: The total sample was composed of 410 students; their mean age was 9.51±1.94 years. The prevalence of bullying was 56.34%. Studen

Background: Birth defects are the leading cause of both neonatal and post-neonatal deaths, as an estimated 240,000 neonates die in their first month of life worldwide each year. In Iraq, local studies have shown varying frequencies and types of congenital anomalies. Objectives: To provide new insight into the incidence and types of congenital anomalies and to explore their possible risk factors in Baghdad City. Methods: In this cross-sectional observational study, a total of 2007 neonates were enrolled from six hospitals in Baghdad during the period extending between September and December 2020. Hospital records and personal interviews were used for data collection. These data included the neonates' demographic and clinical characte

BACKGROUND: Anemia during pregnancy is still a challenge throughout the world, and it may cause severe health consequences in the maternal and fetal sides. AIM: This study aims to find out the prevalence of maternal anemia and potential adverse outcomes in Iraq. METHODS: In Medical City Tertiary Center in Baghdad, singleton pregnant ladies came for delivery were involved over 6 months’ period. Based on hemoglobin (Hb) readings; they were divided into no anemia group (Hb>11 g/l) and anemia group which were further subdivided into mild, moderate, and severe (Hb =10–10.9, =7.1–9.9, and <7 g/l, respectively). Full history and examination were performed by attending obstetrician and pediatrician for the upcoming babies. RE

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed