Text mining tweets on e-cigarette risks and benefits using machine learning following a vaping related lung injury outbreak in the USA.
- DOI
- 10.1016/j.health.2022.100066
- Published
- 2022 Nov
- Container
- Healthcare analytics (New York, N.Y.)
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1016/j.health.2022.100066,
title = {Text mining tweets on e-cigarette risks and benefits using machine learning following a vaping related lung injury outbreak in the USA.},
author = {Hassan L and Elkaref M and de Mel G and Bogdanovica I and Nenadic G},
year = {2022},
journal = {Healthcare analytics (New York, N.Y.)},
doi = {10.1016/j.health.2022.100066},
url = {https://doi.org/10.1016/j.health.2022.100066}
}RIS
TY - JOUR TI - Text mining tweets on e-cigarette risks and benefits using machine learning following a vaping related lung injury outbreak in the USA. AU - Hassan L AU - Elkaref M AU - de Mel G AU - Bogdanovica I AU - Nenadic G PY - 2022 JO - Healthcare analytics (New York, N.Y.) DO - 10.1016/j.health.2022.100066 UR - https://doi.org/10.1016/j.health.2022.100066 ER -
APA
L, H., M, E., G, D. M., I, B., & G, N. (2022). Text mining tweets on e-cigarette risks and benefits using machine learning following a vaping related lung injury outbreak in the USA.. Healthcare analytics (New York, N.Y.). https://doi.org/10.1016/j.health.2022.100066
Source records
- pubmed · retrieved 2026-09-26T11:52:15.298Z