Cervical Uterine Cancer is a disease that explains the vulnerability in which women are in terms of reproductive health with an impact on occupational health and public health, even when in Mexico the prevalence rate is lower than the other member countries of the OECD, its impact on Human Development and Local Development shows the importance that the disease have in communities more than in cities where prevention policies through check-ups and medical examinations seem to curb the trend, but show the lack of opportunities and capacities of health centers in rural areas.   To establish the reliability, validity, and correlations between the variables reported in the literature with respect to their weighting in a public hospital. A

Objective: To assess the impact of pregnant women’s depression state upon their pregnancy outcome Methodology: A descriptive purposive study was used to assess the impact of pregnant women’s depression state on their pregnancy outcomes. The study was conducted from (22nd \ September \ 2020 to 15th \ February \ 2021). A non-probability sample (purposive sample) was selected from 100 women. Data were collected through an interview with the mother in the counseling clinic, during the third trimester of pregnancy, as well as after childbirth in the labour wards to assess the outcome of pregnancy. Data were analyzed through descriptive statistics (frequency and percentages). Results: The most important thing observed in this study was the ne

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Article information: COVID-19 has roused the scientic community, prompting calls for immediate solutions to avoid the infection or at least reduce the virus's spread. Despite the availability of several licensed vaccinations to boost human immunity against the disease, various mutated strains of the virus continue to emerge, posing a danger to the vaccine's ecacy against new mutations. As a result, the importance of the early detection of COVID-19 infection becomes evident. Cough is a prevalent symptom in all COVID-19 mutations. Unfortunately, coughing can be a symptom of various of diseases, including pneumonia and inuenza. Thus, identifying the coughing behavior might help clinicians diagnose the COVID-19 infection earlier and distinguish

Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien

Abstract:

Objectives: To assess nurses' attitude toward end of life phase. To find out  relationships between nurses attitude and socio demographic data (age, gender, level of education, years of experience).

Methodology: A descriptive cross-sectional study design is carried out to assess the attitude on nurses concerning patient at the end of life phase at critical care units, from the period of (1^nd November 2021) to (1^th February 2022). A probability sample random sampling technique used. Then, the number of participants in Baquba Teaching Hospital and general al khalis hospital were determined by using rando

Planning of cities show great attention on streets planning as one of the most structural component foundations for cities, that providing many functional needs and connect parts of the city each other, and work as a commercial and services activities centers. Instead of this highly focused on distributing streets with different streets types such as economical and trading and housing streets. This concerned was only on the dimensions and scales of different types of vehicles and their movement. When scale and dimension and movement of mans were as a second priority in designing and planning streets. Which came's first for traditional streets. The research try to submit some designs guides for planners that contribute in re conce

Background: the early identification of developmental disabilities allows intervention at the earliest possible point to
improve the developmental potential.
Objective: Identify the scope of knowledge of nurses toward signs of gross motor delay for children and its relation to
their demographic characteristics.
Methodology: A descriptive study design was conducted at (18) primary health care centers in first of the primary
health care sector of Alhawija District in Kirkuk Governorate. This study started from September 2010 to the end of
January 2011, in order to identify the level of nurses' knowledge toward signs of gross motor delay for children in
primary health care centers. Non probability (purposive) sample of