Machine learning approaches in COVID-19 diagnosis, mortality, and severity risk prediction: A review.

ABSTRACT: The existence of widespread COVID-19 infections has prompted worldwide efforts to control and manage the virus, and hopefully curb it completely. One important line of research is the use of machine learning (ML) to understand and fight COVID-19. This is currently an active research field. Although there are already many surveys in the literature, there is a need to keep up with the rapidly growing number of publications on COVID-19-related applications of ML. This paper presents a review of recent reports on ML algorithms used in relation to COVID-19. We focus on the potential of ML for two main applications: diagnosis of COVID-19 and prediction of mortality risk and severity, using readily available clinical and laboratory data. Aspects related to algorithm types, training data se

SUBMITTER: Alballa N 

PROVIDER: S-EPMC8018906 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature