This paper is in the following e-collection/theme issue:

e-Learning and Digital Medical Education (769) Substance and Alcohol Abuse in Adolescence (117) Machine Learning (1666) Substance Abuse (451) Mental Health Surveillance and Epidemiology (75) Harm Reduction Approaches (31)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62805, first published .
Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study

Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study

Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study

Authors of this article:

Soeun Kim1, 2 Author Orcid Image ;   Hyejun Kim1, 3 Author Orcid Image ;   Seokjun Kim1, 4 Author Orcid Image ;   Hojae Lee1 Author Orcid Image ;   Ahmed Hammoodi5 Author Orcid Image ;   Yujin Choi1, 6 Author Orcid Image ;   Hyeon Jin Kim1, 2 Author Orcid Image ;   Lee Smith7 Author Orcid Image ;   Min Seo Kim8 Author Orcid Image ;   Guillaume Fond9 Author Orcid Image ;   Laurent Boyer9 Author Orcid Image ;   Sung Wook Baik10 Author Orcid Image ;   Hayeon Lee1, 11 Author Orcid Image ;   Jaeyu Park1, 2 Author Orcid Image ;   Rosie Kwon1 Author Orcid Image ;   Selin Woo1, 4 Author Orcid Image ;   Dong Keon Yon1, 2, 4, 12 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Soeun Kim   1, 2 * , MS ;   Hyejun Kim   1, 3 * , BS ;   Seokjun Kim   1, 4 * , MD ;   Hojae Lee   1 , MS ;   Ahmed Hammoodi   5 , BBA ;   Yujin Choi   1, 6 , BS ;   Hyeon Jin Kim   1, 2 , PhD ;   Lee Smith   7 , PhD ;   Min Seo Kim   8 , MD ;   Guillaume Fond   9 , MD, PhD ;   Laurent Boyer   9 , MD, PhD ;   Sung Wook Baik   10 , PhD ;   Hayeon Lee   1, 11 , PhD ;   Jaeyu Park   1, 2 , PhD ;   Rosie Kwon   1 , MS ;   Selin Woo   1, 4 , PhD ;   Dong Keon Yon   1, 2, 4, 12 , MD, PhD

1 Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Seoul, Republic of Korea

2 Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, Republic of Korea

3 Department of Applied Information Engineering, Yonsei University, Seoul, Republic of Korea

4 Department of Medicine, Kyung Hee University College of Medicine, Seoul, Republic of Korea

5 Department of Business Administration, Kyung Hee University School of Management, Seoul, Republic of Korea

6 Department of Korean Medicine, Kyung Hee University College of Korean Medicine, Seoul, Republic of Korea

7 Centre for Health, Performance and Wellbeing, Anglia Ruskin University, Cambridge, United Kingdom

8 Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, United States

9 Research Centre on Health Services and Quality of Life, Assistance Publique-Hopitaux de Marseille, Aix Marseille University, Marseille, France

10 Department of Software, Sejong University College of Electronics and Information Engineering, Seoul, Republic of Korea

11 Department of Electronics and Information Convergence Engineering, Kyung Hee University, Seoul, Republic of Korea

12 Department of Pediatrics, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Dong Keon Yon, MD, PhD
  • Department of Pediatrics
  • Kyung Hee University Medical Center
  • Kyung Hee University College of Medicine
  • 23 Kyungheedae-ro, Dongdaemun-gu
  • Seoul, 02447
  • Republic of Korea
  • Phone: 82 269352476
  • Fax: 82 5044780201
  • Email: yonkkang@gmail.com