Remote sensing of alcohol consumption using machine learning speckle pattern analysis
Our binary classification model C can successfully distinguish between pre- and post-alcohol consumption with high sensitivity and accuracy. This performance is particularly valuable for clinical and forensic applications, where minimizing false negatives is crucial.
Authors
- Marianna Beiderman (ORCID: https://orcid.org/0000-0003-0110-121X)
- Nisan Ozana (ORCID: https://orcid.org/0000-0001-6025-3243)
- Sergey Agdarov (ORCID: https://orcid.org/0000-0003-4098-6815)
- Doron Duadi (ORCID: https://orcid.org/0000-0003-3524-1907)
- Yevgeny Beiderman
- Zeev Zalevsky (ORCID: https://orcid.org/0000-0002-4459-3421)
- Avraham Yosovich
Institutions
- Bar-Ilan University (IL)
- Holon Institute of Technology (IL)
- Ruppin Academic Center (IL)
Publication Details
- Journal
- Journal of Biomedical Optics
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1117/1.jbo.30.3.037001
- Citations
- 1
- Primary Topic
- Spectroscopy and Chemometric Analyses
- Type
- article
- Field-Weighted Citation Impact
- 0.75