Machine learning prediction of blood alcohol concentration: a digital signature of smart-breathalyzer behavior
Abstract Excess alcohol use is an important determinant of death and disability. Machine learning (ML)-driven interventions leveraging smart-breathalyzer data may help reduce these harms. We developed a digital phenotype of long-term smart-breathalyzer behavior to predict individuals’ breath alcohol...
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Autores principales: | Kirstin Aschbacher, Christian S. Hendershot, Geoffrey Tison, Judith A. Hahn, Robert Avram, Jeffrey E. Olgin, Gregory M. Marcus |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/68cb6f10c04a437287ff26a0b88550f1 |
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