Machine‐learning prediction of adolescent alcohol use: a cross‐study, cross‐cultural validation-Reference-Cited by-同舟云学术

Machine‐learning prediction of adolescent alcohol use: a cross‐study, cross‐cultural validation

Published:2018-12-21 Issue:4 Volume:114 Page:662-671
ISSN:0965-2140
Container-title:Addiction
language:en
Short-container-title:Addiction

Author:

Afzali Mohammad H.¹^ORCID,Sunderland Matthew²,Stewart Sherry³,Masse Benoit¹,Seguin Jean¹,Newton Nicola²,Teesson Maree²,Conrod Patricia¹

Affiliation:

1. Department of PsychiatryUniversity of Montreal Montréal QC Canada

2. National Drug and Alcohol Research CentreUniversity of New South Wales Randwick NSW Australia

3. Department of PsychiatryDalhousie University Life Sciences Centre—Psychology Halifax NS Canada

Funder

Institute of Neurosciences, Mental Health and Addiction

Canadian Institutes of Health Research

Publisher

Wiley

Subject

Psychiatry and Mental health,Medicine (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/add.14504

Reference52 articles.

1. Guidelines and challenges for estimating the economic costs and benefits of adolescent substance abuse treatments

2. The Economic Impact of Attention-Deficit/Hyperactivity Disorder in Children and Adolescents

3. Adolescent Substance Use

4. JohnstonLD O'MalleyPM BachmanJG MiechMA SchulenbergJE.Monitoring the Future National Survey Results On Drug Use 1975–2015. Overview Key Findings on Adolescent Drug Use. Ann Arbor: Institute for Social Research The University of Michigan;2016.

5. Childhood and adolescent predictors of alcohol use and problems in adolescence and adulthood in the National Child Development Study

Cited by 38 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparing four algorithms in predicting the risk of driving under the influence of alcohol among individuals with alcohol use disorder;Current Psychology;2024-06-11

2. Regression tree applications to studying alcohol-related problems among college students.;Experimental and Clinical Psychopharmacology;2024-05-02

3. Comparison of Optimized Random Forest Classifier with K-Nearest Neighbors Classifier to Determine the Factors Influencing Teenagers Alcoholic Consumption;2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM);2024-04-04

4. How machine learning is used to study addiction in digital healthcare: A systematic review;International Journal of Information Management Data Insights;2023-11

5. AUD-DSS: a decision support system for early detection of patients with alcohol use disorder;BMC Bioinformatics;2023-09-02