Although there is a significant influence of implementing the electronic health records (EHR) system in Qatar, there are very limited studies reviewed and analyzed the influence of implementing the EHR system on healthcare professionals in Qatar. This research aims to assess, summarize, and analyze the influence of the EHR system in healthcare settings in Qatar. The outcome of assessing the implementation of the EHR system may have advantages and disadvantages, which can impact healthcare professionals in healthcare settings in Qatar. The main objective is to evaluate EHR on healthcare professionals in healthcare. A total number of 210 participants were selected randomly from three private hospitals in Qatar. A validated survey distributed to physicians, pharmacists, nurses, and dietitians who work in these healthcare hospitals in Qatar. The purpose is to identify whether the outcome of using the EHR system improved healthcare professionals’ work after it has shifted from using files and hand-writing paperwork to the EHR system. By applying online survey, results indicate that most healthcare professionals positively perceive the use of the EHR system as a valuable system.
During the ongoing worldwide crisis, researchers, clinicians, and medical care specialists around the world continue looking for another innovation to help in handling the COVID-19 pandemic. The proof of Machine Learning (ML) and Artificial Intelligence (AI) application on the past pestilence empower scientists by giving another point to battle against the novel Coronavirus episode. This paper intends to thoroughly audit the part of AI and ML as one critical technique in anticipating SARS-CoV-2 and its related epidemic. Coronavirus is an irresistible illness, and it does serious harm to the lungs. Coronavirus causes disease in people and has executed numerous individuals in the whole world. Nonetheless, this infection is accounted for as a pandemic by the World Health Organization. (WHO) and all nations are attempting to control and lockdown all spots. This work's main principle goal is to predicting the spread of COVID-19 across Egypt and analyzing the development rates. For this aim, we access real datasets collected from Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). And European Union open dataset. We have implemented the results by using R Language.
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