Machine learning approach to examine the intersectional association of social identities and circumstance with current cigarette smoking among US adults.
- DOI
- 10.1093/jncimonographs/lgaf001
- Published
- 2025 Aug 1
- Container
- Journal of the National Cancer Institute. Monographs
- 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:10.1093/jncimonographs/lgaf001,
title = {Machine learning approach to examine the intersectional association of social identities and circumstance with current cigarette smoking among US adults.},
author = {Choi K and Wheeler W and Ravichandran S and Buckman DW},
year = {2025},
journal = {Journal of the National Cancer Institute. Monographs},
doi = {10.1093/jncimonographs/lgaf001},
url = {https://doi.org/10.1093/jncimonographs/lgaf001}
}RIS
TY - JOUR TI - Machine learning approach to examine the intersectional association of social identities and circumstance with current cigarette smoking among US adults. AU - Choi K AU - Wheeler W AU - Ravichandran S AU - Buckman DW PY - 2025 JO - Journal of the National Cancer Institute. Monographs DO - 10.1093/jncimonographs/lgaf001 UR - https://doi.org/10.1093/jncimonographs/lgaf001 ER -
APA
K, C., W, W., S, R., & DW, B. (2025). Machine learning approach to examine the intersectional association of social identities and circumstance with current cigarette smoking among US adults.. Journal of the National Cancer Institute. Monographs. https://doi.org/10.1093/jncimonographs/lgaf001
Source records
- pubmed · retrieved 2026-11-10T14:42:04.305Z
- europe-pmc · retrieved 2026-11-10T14:42:04.308Z