Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are complex images in their interpretation. In this article, two deep convolutional neural network (DCNN) classifiers, such as Inception-v2 and VGG-16, are utilized to detect COVID-19 from a set of chest X-ray images. The dataset for this article was collected from the Kaggle platform (COVID-19 Radiography Database) and consists of images of positive and healthy people. This article concludes that the most suitable performance is the Inception-v2 classifier, which has achieved an accuracy of 97% in comparison to the VGG-16 classifier, which has achieved an accuracy of 93%.
The first known use of the term conspiracy theory dated back to the nineteenth century. It is defined as a theory that explains an event or set of circumstances as the result of a secret plot by usually powerful conspirators. It is commonly used, but by no means limited to, extreme political groups. Since the emergence of COVID-19 as a global pandemic in December 2019, the conspiracy theory was present at all stages of the pandemic.
The coronavirus disease 2019 (COVID-19) pandemic and the infection escalation around the globe encourage the implementation of the global protocol for standard care patients aiming to cease the infection spread. Evaluating the potency of these therapy courses has drawn particular attention in health practice. This observational study aimed to assess the efficacy of Remdesivir and Favipiravir drugs compared to the standard care patients in COVID-19 confirmed patients. One hundred twenty-seven patients showed the disease at different stages, and one hundred and fifty patients received only standard care as a control group were included in this study. Patients under the Remdesivir therapy protocol were (62.20%); meanwhile, there (30.71
... Show MoreThe largest use of x-ray in medical by dentists, employers or persons that needed by patients with specific conditions, lead to higher exposure of x-ray that may cause many diseases. In the present work radiography films have been used in evaluating the efficiency of using unsaturated polyester polymer reinforced with lead oxide (PbO) as shield material for medical x-ray devices, many parameters studied like concentration and thickness that they are increasing the attenuation of x-ray in them. The results show that the attenuation of X-ray increasing with concentration of reinforced material and with thickness, and the optical density decreases with increasing concentration from 0% to 50%, we chose 30% as suitable concentration to increase
... Show MoreDifferent bremsstrahlung spectra from tungsten anode x-ray tube generated at 30, 40 and 50 kV have been examined theoretically and experimentally for an attempt to find a most suitable spectrum to radiograph a test object of 0.01 cm thickness of Cu and Ag. The high contrast using this suitable spectrum is demonstrated and the possible effects of fluorescent radiation are discussed.
The unresolved COVID‐19 pandemic considerably impacts the health services in Iraq and worldwide. Consecutive waves of mutated virus increased virus spread and further constrained health systems. Although molecular identification of the virus by polymerase chain reaction is the only recommended method in diagnosing COVID‐19 infection, radiological, biochemical, and hematological studies are substantially important in risk stratification, patient follow‐up, and outcome prediction.
This narrative review summarized the hematological changes including the blood indices, coagulative indicator
Keywords provide the reader with a summary of the contents of the document and play a significant role in information retrieval systems, especially in search engine optimization and bibliographic databases. Furthermore keywords help to classify the document into the related topic. Keywords extraction included manual extracting depends on the content of the document or article and the judgment of its author. Manual extracting of keywords is costly, consumes effort and time, and error probability. In this research an automatic Arabic keywords extraction model based on deep learning algorithms is proposed. The model consists of three main steps: preprocessing, feature extraction and classification to classify the document
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BACKGROUND: A novel coronavirus officially recognized as SARS-CoV2, first emerged in Wuhan, China, has allowed COVID-19 to rapidly spread. The WHO declared the global pandemic of COVID-19 a public health emergency of international concern. Early evaluation of the mental health of healthcare workers (HCWs) and consideration of effective therapeutic strategies is important. OBJECTIVE: To assess the mental status (depression and anxiety) among HCWs and identify the association between depression, anxiety levels and (certain demographic factors and other factors). PATIENTS AND METHODS: A cross-sectional study was conducted on data collected |
Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras
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