Identifying Patterns of Tobacco Use and Associated Cardiovascular Disease Risk Through Machine Learning Analysis of Urine Biomarkers
Our categorization of exposure through cluster analysis provides a potential tool for evaluating the use of emerging tobacco products and establishing a connection between novel exposures and cardiovascular risk. This approach may contribute to the validation of a valuable tool for assessing the risk associated with the use of different tobacco products.
Authors
- Noah Siegel (ORCID: https://orcid.org/0000-0002-9046-8656)
- Aruni Bhatnagar (ORCID: https://orcid.org/0000-0001-6818-0384)
- Andrew Stokes (ORCID: https://orcid.org/0000-0002-8502-3636)
- Emelia J. Benjamin (ORCID: https://orcid.org/0000-0003-4076-2336)
- Jennifer L. Hall (ORCID: https://orcid.org/0000-0002-5103-5399)
- Juan Zhao (ORCID: https://orcid.org/0000-0002-8633-0072)
Institutions
- Boston University (US)
- American Heart Association (US)
- Boston Medical Center (US)
Publication Details
- Journal
- JACC Advances
- Published
- 2025-02-22
- DOI
- https://doi.org/10.1016/j.jacadv.2025.101630
- Citations
- 1
- Primary Topic
- Cardiovascular Health and Risk Factors
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- American Heart Association
- American Lung Association
- National Heart, Lung, and Blood Institute
- Center for Tobacco Products