This research aims to investigate the approaches adopted by Iraqi newspapers in addressing the COVID-19 pandemic crisis. Employing a descriptive methodology and survey technique, the study conducts content analysis on articles published in three prominent newspapers: Al-Sabah, Al-Mada, and Tareeq Al-Shaab. A multi-stage sampling method was employed, encompassing 260 issues of the aforementioned newspapers. Data collection involved the use of a content analysis questionnaire, with the "How it was said?" method utilized to determine analysis categories.
The results showed that Al-Sabah newspaper adopted a positive approach in addressing COVID-19-related topics, while Al-Mada newspaper remained neutral, and Tare

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

By March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy

Objective(s): to assess the factors which are associated with the prolonged prehospital delay of patients with
acute myocardial infarction.
Methodology: A descriptive study was conducted at the Coronary Care unit (CCU) in Al-Yarmok Teaching
Hospital, Ibn AL-Nafis Hospital for Cardiovascular Diseases, AL-Kadumia Teaching Hospital, Baghdad Teaching
Hospital, and AL-Kindy Teaching Hospital during the period of the study from February 2
nd
, 2009 to October 30th
,
2009. A random sample of (160) paƟent who were admiƩed to the hospitals were selected one by one. A
questionnaire was constructed for the purpose of the study, which is comprised of four parts that include (1)
sociodemographic data; (2) prehospital d

Fibroblast growth factors-23 (FGF-23) are a class of cell signaling proteins produced by macrophages. They have a range of roles, but they play a particularly important role in the development of animal cells, where they are essential for appropriate growth. Phosphate, which is found in the body as both organic and mineral phosphate, plays crucial roles in cell structure, communication, and metabolism. Most phosphate in the body resides in bone, teeth, and inside cells, with less than 1% circulating in serum. The aim of the study is to evaluate the levels of the Fibroblast Growth Factors-23 and phosphate and receiver operating characteristic (ROC) in acromegaly patients against healthy control. A case control study Fibroblast Growth Fact

‎  Since the first outbreak in Wuhan, China, in December 31, 2019, COVID-19    pandemic  ‎has been spreading to many countries in the world. The ongoing COVID-19 pandemic has caused a ‎major global crisis, with 554,767 total confirmed cases, 484,570 total recovered cases, and ‎‎12,306 deaths in Iraq as of February 2, 2020. In the absence of any effective therapeutics or drugs ‎and with an unknown epidemiological life cycle, predictive mathematical models can aid in ‎the understanding of both control and management of coronavirus disease. Among the important ‎factors that helped the rapid spread of the ep

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