After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Background: Pregnancy is a natural physiological state that involves several biochemical modifications. Saliva is consisted of many types of proteins such as salivary alpha amylase and salivary peroxidase that might be affected by pregnancy. The former enzyme is considered one of the most prevalent proteins that is released by highly differentiated epithelial acinar cells and has been shown to have enzymatic activities while the latter has been approved that it  has a significant role in oral health. The purpose of this study was to the evaluate the salivary levels of alpha-amylase and peroxidase in pregnant and non-pregnant women. Materials and Methods: Sixty pregnant women were grouped according to the pregnancy trimesters. The first

Back ground: Anaemia is one of commonest health problems in antenatal care units of developing countries and contributes significantly to increased maternal and fetal morbidity and mortality.
Patients and methods: During the period from 1st of July 2007 to the end of October 2007, hundred anaemic pregnant women attending the gynaecology and obstetrics department in Al- Yarmook teaching hospital in Baghdad and 20 apparently healthy pregnant women,aged between 17 - 46 years as a control were included in this study. Anaemic women included in this study fulfilled the criteria of haemoglobin concentration of less than 110 g/L in first trimester and 105g/L in the second and third trimesters, no history of acute

      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

Background: Urinary tract infection (UTI) is the most common disease associated with pregnant women due to several anatomical and hormonal changes in pregnant women lead to ureteral dilatation and urinary infection, many of microorganisms such as fungi, viruses, and bacteria have numerous virulence factors that enhance their ability to colonize in pregnant women. Some bacteria have resistance toward many antimicrobial agents for treatment has led to therapeutic difficulties worldwide, in order that many investigators try to test fungal extract to reduce bacterial infection.

Objectives: To assess the effectiveness of extract of Calvatia craniiformis on different types of bacteria which wa

There is limited data and evidence about the effects of COVID-19 on Maternal health, especially when new information is emerging daily, through pregnancy, child birth and post natal period, women are vulnerable to have the infection, this article, aimed to show the suitable measures that should be applied for women at reproductive age who are suspected /confirmed with COVID -19 infection,

During pregnancy it is advisable to continue the antenatal care schedule, although reducing face to face visit is recommended (unless the pregnant condition required that ),and prioritize ANC at health facilities for high-risk pregnancy and during second half of pregnancy with adequate infection prevention control  measures.

Regardi

Factor analysis is distinguished by its ability to shorten and arrange many variables in a small number of linear components. In this research, we will study the essential variables that affect the Coronavirus disease 2019 (COVID-19), which is supposed to contribute to the diagnosis of each patient group based on linear measurements of the disease and determine the method of treatment with application data for (600) patients registered in General AL-KARAMA Hospital in Baghdad from 1/4/2020 to 15/7/2020. The explanation of the variances from the total variance of each factor separately was obtained with six elements, which together explained 69.266% of the measure's variability. The most important variable are cough, idleness, fever, headach

Background: Osteoporosis is a progressive systemic skeletal disorder characterized by low bone mass and micro-architectural deterioration of bone tissue spatially in postmenopausal women and its major complication fractures.
Objective: The aim of this study was to find out the significance of serum OC and serum OPN levels with the incidence of osteoporosis and its major complication (fractures).
Patients and Methods: Eighty-five postmenopausal women (PMW) whose ages were fifty years and over categorized into three groups: osteoporosis PMW without VFs (n=30), osteoporosis PMW with VFs (n=28), and healthy PMW (n=27). Sera samples were analyzed for alkaline phosphatase, calcium and phosphorous by using spectrophotometric kit. Serum OC

Pro-inflammatory cytokines play an important role in intercellular communications. In the last two decades, many cytokines have been identified in human milk. These cytokines are variable according to different conditions such as pathogenic infections which strongly stimulated the immune response. The present study aims to determine of IL1β and TNF-α in Toxoplasma gondii-free and infected women in an attempt to clarify the impacts of the infections on cytokines especially in mother's milk. The serum and milk sample were collected from 96 samples (48 for seropositive and 48 for seronegative). To confirm the Toxoplasma gondii infection; enzyme linked immunofluorescence assay (ELIFA) was used to detect anti-Toxoplasma Ig