جستجوی مقالات مرتبط با کلیدواژه « Coronavirus disease » در نشریات گروه « علوم پایه »

In this review, we will discuss the neuroimaging findings of patients with COVID-19 from the outbreak (late December 2019) to the end of October 2021. PubMed, Scopus, Google Scholar, Science Direct, ProQuest, Web of Science and the World Health Organization database (January 01, 2020, to October 30, 2021) were searched for related published articles. In each of the databases, the appendix search strategies were performed and the below keywords were used: COVID-19”OR“coronavirus disease 2019” AND “brain MRI” OR “brain magnetic resonance imaging” OR “brain CT” OR “neuroimaging”. In total, neuroimaging findings of 1550 patients, with ages from 1-96 years, were analyzed. Most brain neuroimaging findings include hyperintensity, Cerebral venous thrombosis, intraventricular and subarachnoid hemorrhage, infarction, leukoencephalopathy, acute ischemic strokes and posterior reversible encephalopathy syndrome (PRES) in adult patients and severe encephalopathy, stroke, infarction, CNS infection/demyelination, neuritis or polyradiculitis, venous thrombosis, Guillain-Barré syndrome, and longitudinally extensive myelitis, and myositis in pediatric patients. Our findings showed that the most important complication of the coronavirus is not just respiratory complications, because although transiently, COVID-19-related brain complications are seen in pediatrics as well as adults, and families should pay more attention to health care.

COVID-19, an epidemic disease, has challenged human lives all over the world. Governments and scientific communities are trying their level best to help the masses. This disease which is caused by corona virus majorly attacks the upper respiratory system rendering the human immunity incapacitated and, in some cases, proving fatal. Therefore, it is very much important to identify the infected people quickly and accurately, so that it can be prevented from spread. Early addressal of the symptoms can help to prevent the disease to become severe for all mankind. This calls for the development of a decision-making system to help the medical fraternity for the timely action. This proposed fuzzy based system predicts Covid-19 based on individuals’ symptoms and parameters. It receives input parameters as fever, cough, breathing difficulty, muscle ache, sore throat, travel history, age, medical history in the form of different membership functions and generates one output that predicts the likelihood of a person being infected with COVID-19 using Mamdani fuzzy inference system. The timely prognosis of the disease at home isolation or at the security checks can help the patient to seek the medical treatment as early as possible. Patient case studies, real time observations, cluster cases were studied to create the rule base for FDMS. The results are validated by using real-time individuals test cases on the proposed system which yields 97.2% accuracy, 100% sensitivity and 96.2% specificity.

In this work, a researcher develop $SHEIQRD$ (Susceptible-Stay at home-Exposed-Infected-Quarantine-Recovery-Death) coronavirus pandemic spread model. The disease-free and endemic equilibrium points are calculated and analyzed. The basic reproductive number $R_0$ is derived and its sensitivity analysis is done. COVID-19 pandemic spread is die out when $R_0leq 1$ and its persist in the community whenever $R_0>1$. More than $10%$ of lockdown or home quarantine, above $50%$ and $30%$ identification and isolation of expose and infected individuals respectively, and reduction home quarantine return rate(less than $10%$) can be mitigates the pandemics. Finally, theoretical analysis and numerical results are consistent.