Use of Artificial Intelligence for Predicting COVID-19 Outcomes: A Scoping Review

Jinyan Lyu, Wanting Cui, Joseph Finkelstein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


During the COVID-19 pandemic, artificial intelligence has played an essential role in healthcare analytics. Scoping reviews have been shown to be instrumental for analyzing recent trends in specific research areas. This paper aimed at applying the scoping review methodology to analyze the papers that used artificial intelligence (AI) models to forecast COVID-19 outcomes. From the initial 1,057 articles on COVID-19, 19 articles satisfied inclusion/exclusion criteria. We found that the tree-based models were the most frequently used for extracting information from COVID-19 datasets. 25% of the papers used time series to transform and analyze their data. The largest number of articles were from the United States and China. The reviewed artificial intelligence methods were able to predict cases, death, mortality, and severity. AI tools can serve as powerful means for building predictive analytics during pandemics.

Original languageEnglish
Title of host publicationInformatics and Technology in Clinical Care and Public Health
EditorsJohn Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias, Joseph Liasko
PublisherIOS Press BV
Number of pages4
ISBN (Electronic)9781643682501
StatePublished - 2022

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


  • Artificial Intelligence
  • COVID-19
  • Scoping Review


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