Using machine learning to predict pretreatment drinking changes

The identification of demographic variables as important predictors highlights the importance of understanding demographic and societal-level factors as potential drivers of pretreatment drinking changes.

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Publication Details

Journal
Alcohol Clinical and Experimental Research
Published
2026-02-01
DOI
https://doi.org/10.1111/acer.70244
Primary Topic
Substance Abuse Treatment and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
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article

Using machine learning to predict pretreatment drinking changes

Matison W. McCool, Stephen A. Maisto, Robert C. Schlauch
Alcohol Clinical and Experimental Research
Substance Abuse Treatment and Outcomes
article

Using machine learning to predict pretreatment drinking changes

Matison W. McCool, Stephen A. Maisto, Robert C. Schlauch
article en

Abstract

The identification of demographic variables as important predictors highlights the importance of understanding demographic and societal-level factors as potential drivers of pretreatment drinking changes.

Alcohol Clinical and Experimental ResearchVol. 50(2)
University of New Mexico (US), University of South Florida (US), Syracuse University (US)
No poverty
Openalex Percentile: Top 59%
Substance Abuse Treatment and Outcomes
DOISourceOpenAlex
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