Statins: Could an old friend help in the fight against COVID-19?
Ontology highlight
ABSTRACT:
SUBMITTER: Rodrigues-Diez RR
PROVIDER: S-EPMC7323198 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: In December 2019, the novel Coronavirus disease (COVID-19) broke out in Wuhan, China leading to major national and international disruptions in healthcare, business, education, transportation, and nearly every aspect of our daily lives. Artificial Intelligence (AI) has been leveraged amid the COVID-19 pandemic, however, little is known about its use for supporting public health efforts.Objective: The scoping review aimed to explore how AI technology is being used during the COVID-19 pandemic, as reported in the literature. Thus, it is first review that describes and summarizes features of the identified AI techniques and datasets used for their development and validation.Methods: A scoping review was conducted following the guidelines of PRISMA Extension for Scoping Reviews (PRISMA-ScR). We searched the most commonly used electronic databases (e.g., MEDLINE, EMBASE, PsycInfo) between April 10 and 12, 2020. These terms were selected based on the target intervention (i.e., AI) and the target disease (i.e., COVID-19). Two reviewers independently conducted study selection and data extraction. A narrative approach was used to synthesize the extracted data.Results: We considered 82 studies out of the 435 retrieved studies. The most common use of AI was diagnosing COVID-19 cases based on various indicators. AI was also employed in drug and vaccine discovery or repurposing, and assessing their safety. Further, the included studies used AI for forecasting the epidemic development of COVID-19 and predicting its potential hosts/reservoirs. Researchers utilized AI for patient outcome-related tasks such as assessing the severity of COVID-19, predicting mortality risk, its associated factors, and length of hospital stay. AI was used for Infodemiology to raise awareness to use water, sanitation, and hygiene. The most prominent AI techniques used were Convolutional Neural Network (CNN) followed by Support Vector Machine (SVM).Conclusions: The included studies showed that AI has the potential to fight against COVID-19. However, many of the proposed methods are not yet clinically accepted. Thus, the most rewarding research will be on methods promising value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for studies on AI.
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Project description:Coronavirus disease 2019 (COVID-19) has developed as a pandemic, and it created an outrageous effect on the current healthcare and economic system throughout the globe. To date, there is no appropriate therapeutics or vaccines against the disease. The entire human race is eagerly waiting for the development of new therapeutics or vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Efforts are being taken to develop vaccines at a rapid rate for fighting against the ongoing pandemic situation. Amongst the various vaccines under consideration, some are either in the preclinical stage or in the clinical stages of development (phase-I, -II, and -III). Even, phase-III trials are being conducted for some repurposed vaccines like Bacillus Calmette-Guérin, polio vaccine, and measles-mumps-rubella. We have highlighted the ongoing clinical trial landscape of the COVID-19 as well as repurposed vaccines. An insight into the current status of the available antigenic epitopes for SARS-CoV-2 and different types of vaccine platforms of COVID-19 vaccines has been discussed. These vaccines are highlighted throughout the world by different news agencies. Moreover, ongoing clinical trials for repurposed vaccines for COVID-19 and critical factors associated with the development of COVID-19 vaccines have also been described.
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