@inproceedings{d8ab5d743e0246c6aa7c2881090628fb,
title = "Use of Artificial Intelligence for Predicting COVID-19 Outcomes: A Scoping Review",
abstract = "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.",
keywords = "Artificial Intelligence, COVID-19, Scoping Review",
author = "Jinyan Lyu and Wanting Cui and Joseph Finkelstein",
note = "Publisher Copyright: {\textcopyright} 2022 The authors and IOS Press.",
year = "2022",
doi = "10.3233/SHTI210923",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "317--320",
editor = "John Mantas and Arie Hasman and Househ, {Mowafa S.} and Parisis Gallos and Emmanouil Zoulias and Joseph Liasko",
booktitle = "Informatics and Technology in Clinical Care and Public Health",
address = "Netherlands",
}