Open AccessArtificial intelligence as a powerful tool in overcoming substantial health problems of the COVID-19 pandemic
Author(s) -
Vukoman Jokanović,
Marija Živković,
Slavoljub Živković
Publication year - 2021
Publication title -
stomatološki glasnik srbije
Language(s) - English
Resource type - Journals
eISSN - 1452-3701
pISSN - 0039-1743
DOI - 10.2298/sgs2103143j
Subject(s) - artificial intelligence , covid-19 , scopus , medline , computer science , applications of artificial intelligence , pandemic , machine learning , medicine , disease , infectious disease (medical specialty) , pathology , political science , law
. This review aims to investigate modern methods of applying artificial intelligence to diagnose SARS Cov-2 and predict the development of potential emergencies. Methods. The most commonly used electronic databases, such as Scopus and Medline during 2020, were searched. A narrative approach was used to synthesize the extracted data. Results. In this review paper, it has been shown that the application of artificial intelligence plays a significant role in virus diagnosis and prognosis in clinical trials. It allows resources to be used much more rationally, such as respirators, in hospitals, during the treatment of SARS Cov-2 and the prediction of possible mortality. The obtained results are from the analysis performed on 120 papers and studies that were electronically taken from papers published on Scopus and Pub Med line. Most commonly used artificial intelligence techniques are convolutional neural networks and machine learning. Conclusions. Included studies showed that artificial intelligence can significantly improve the treatment of SARS Cov-2, although many of the proposed methods have not yet been clinically accepted. In addition, more effort is needed to develop standardized reporting protocols or guidelines on applying artificial intelligence into conventional clinical practice. This technology is suitable for fast and accurate diagnosis, prediction and monitoring of current patients and prognosis of disease development in future patients.