<span>Blood donation is the main source of blood resources in the blood banks which is required in the hospitals for everyday operations and blood compensation for the patients. In special cases, the patients require fresh blood for compensation such as in the case of major operations and similar situations. Moreover, plasma transfusions are vital in the current pandemic of coronavirus disease (COVID-19). In this paper, we have proposed a donation system that manages the appointments between the donors and the patient in the case of fresh blood donation is required. The website is designed using the Bootstrap technology to provide suitable access using the PC or the smart phones web browser. The website contains large database

In this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which

Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

       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

the sera levels of luteninizing hormone were investgaited prior tq surgery in 10 postmenopaisal women with benign and 10 postmenopausal women with maliganant healthy

Many studies dealt with the consequences of  SARS CoV-2  (which cause COVID-19 infection) on the nervous system especially sensory nerves where the virus causes loss of taste and smell as it’s known, and may affect auditory nerves and be the expected cause of some hearing problems. A case-control analytic study was performed on a connivance sample of society of university students from a medical faculty. Each participant filled out a questionnaire contains demographic data and general, auditory and respiratory health condition, in addition to vaccination status. In the other side, the audio- examinations were performed on the study sample including Pure Tone Audiometry (PTA) and tympanometry. Two statistical methods; chi-square and t

  Routine vaccination activities, such as detection, reporting, and management of adverse events following immunization (AEFIs), are generally handled by healthcare providers (HCPs). Safe vaccines against severe acute respiratory syndrome coronavirus (SARS-CoV-2) were introduced to control the Coronavirus Disease-19 (COVID-19) pandemic. The study aimed to assess the knowledge, perceptions, and practice of HCPs in Iraq about reporting adverse events following COVID-19 vaccination, and their association with sociodemographic variables. The study was a cross-sectional study that was carried out between August and September 2021 at the COVID-19 vaccination centers in Iraq. This study used an online and paper-based questionnaire, which

The current research aims to identify the degree to which a sample of managers in public organizations appreciated the level of application of the service leadership style from their point of view, and its relationship to the customer satisfaction index in light of the (Covid-19) pandemic, to achieve this, the researcher followed the experimental approach by applying a questionnaire that included two axes, The first: to measure the level of service leadership according to the scale (D. Van Dierendonck and I. Nuijten, 2011), which includes (8) dimensions (empowerment, stand back, accountability, courage, forgiveness, Authenticity, humility, stewardship). The second axis: to measure the level of customer satisfaction according to (Askim, 2004

Biomarkers such as Interleukin-6 (IL-6), Procalcitonin (PCT), C-reactive protein (CRP) and Neutrophil-Lymphocyte Ratio (NLR) have a role in the pathogenesis of severe coronavirus disease 2019 (COVID-19). The aim of this study was to explore the differences between serum levels of such biomarkers in severe and non-severe COVID-19 cases and compare them with normal people and to evaluate the sociodemographic variables and chronic diseases effect on the severity of COVID-19. The study included 160 subjects, divided into two groups, a case group of 80 patients, and a control group of 80 normal persons. The case group was divided into two subgroups: 40 severe COVID-19 patients and 40 patients with non-severe disease. Blood IL-6 was asses