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
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/68cb6f10c04a437287ff26a0b88550f1
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