A Bayesian mixed effects support vector machine for learning and predicting daily substance use disorder patterns-Reference-Cited by-同舟云学术

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A Bayesian mixed effects support vector machine for learning and predicting daily substance use disorder patterns

Published:2022-02-23 Issue:4 Volume:48 Page:413-421
ISSN:0095-2990
Container-title:The American Journal of Drug and Alcohol Abuse
language:en
Short-container-title:The American Journal of Drug and Alcohol Abuse

Author:

Baurley James W.¹,Claus Eric D.²,Witkiewitz Katie³^ORCID,McMahan Christopher S.⁴^ORCID

Affiliation:

1. Data Science, BioRealm LLC, Walnut, CA, USA

2. Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA USA

3. Department of Psychology, University of New Mexico, Albuquerque, NM, USA

4. School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC, USA

Funder

NIH/NIAAA SBIR Phase I

NIH

NSF

Office of Naval Research

Publisher

Informa UK Limited

Subject

Psychiatry and Mental health,Clinical Psychology,Medicine (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/00952990.2021.2024839

Reference37 articles.

1. Heterogeneity of Alcohol Use Disorder: Understanding Mechanisms to Advance Personalized Treatment

2. Neural correlates of alcohol use disorder severity among nontreatment‐seeking heavy drinkers: An examination of the incentive salience and negative emotionality domains of the alcohol and addiction research domain criteria

3. Applied Logistic Regression Analysis

4. Learning classification trees

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