Published on in Vol 23, No 4 (2021): April
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/26628, first published
.
![Machine Learning–Based Prediction of Growth in Confirmed COVID-19 Infection Cases in 114 Countries Using Metrics of Nonpharmaceutical Interventions and Cultural Dimensions: Model Development and Validation Machine Learning–Based Prediction of Growth in Confirmed COVID-19 Infection Cases in 114 Countries Using Metrics of Nonpharmaceutical Interventions and Cultural Dimensions: Model Development and Validation](https://asset.jmir.pub/assets/bebfda33bf5a758de6e1974df1cac715.png 480w,https://asset.jmir.pub/assets/bebfda33bf5a758de6e1974df1cac715.png 960w,https://asset.jmir.pub/assets/bebfda33bf5a758de6e1974df1cac715.png 1920w,https://asset.jmir.pub/assets/bebfda33bf5a758de6e1974df1cac715.png 2500w)
1 Department of Computer Science, University of Toronto, Toronto, ON, Canada
2 Vector Institute for Artificial Intelligence, Toronto, ON, Canada
3 Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
4 Unity Health Toronto, Toronto, ON, Canada