Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study.
- DOI
- 10.2196/38158
- Published
- 2022 Dec 8
- Container
- JMIR public health and surveillance
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.2196/38158,
title = {Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study.},
author = {Thompson HM and Sharma B and Smith DL and Bhalla S and Erondu I and Hazra A and Ilyas Y and Pachwicewicz P and Sheth NK and Chhabra N and Karnik NS and Afshar M},
year = {2022},
journal = {JMIR public health and surveillance},
doi = {10.2196/38158},
url = {https://doi.org/10.2196/38158}
}RIS
TY - JOUR TI - Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study. AU - Thompson HM AU - Sharma B AU - Smith DL AU - Bhalla S AU - Erondu I AU - Hazra A AU - Ilyas Y AU - Pachwicewicz P AU - Sheth NK AU - Chhabra N AU - Karnik NS AU - Afshar M PY - 2022 JO - JMIR public health and surveillance DO - 10.2196/38158 UR - https://doi.org/10.2196/38158 ER -
APA
HM, T., B, S., DL, S., S, B., I, E., A, H., Y, I., P, P., NK, S., N, C., NS, K., & M, A. (2022). Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study.. JMIR public health and surveillance. https://doi.org/10.2196/38158
Source records
- pubmed · retrieved 2026-09-27T08:27:55.953Z