Using machine learning to predict heavy drinking during outpatient alcohol treatment.

Roberts, Walter; Zhao, Yize; Verplaetse, Terril; Moore, Kelly E; Peltier, MacKenzie R; Burke, Catherine; Zakiniaeiz, Yasmin; McKee, Sherry

Roberts, Walter; Zhao, Yize; Verplaetse, Terril; Moore, Kelly E; Peltier, MacKenzie R; Burke, Catherine; Zakiniaeiz, Yasmin; McKee, Sherry.

Affiliation

Roberts W; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Zhao Y; Department of Psychology, East Tennessee State University, Johnson City, Tennessee, USA.
Verplaetse T; Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA.
Moore KE; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Peltier MR; Department of Psychology, East Tennessee State University, Johnson City, Tennessee, USA.
Burke C; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Zakiniaeiz Y; Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA.
McKee S; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.

Alcohol Clin Exp Res ; 46(4): 657-666, 2022 04.

Article in En | MEDLINE | ID: mdl-35420710

Subject(s)

Alcoholism; Outpatients; Alcoholism/diagnosis; Alcoholism/therapy; Algorithms; Ethanol; Female; Humans; Machine Learning; Male; Treatment Outcome

Key words

COMBINE; alcohol use disorder; machine learning; prediction; treatment outcomes

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Outpatients / Alcoholism Type of study: Clinical_trials / Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Male Language: En Journal: Alcohol Clin Exp Res Year: 2022 Document type: Article Affiliation country: United States Country of publication: United kingdom

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