Machine‐Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data

Author:

Zhang‐James Yanli1,Chen Qi2,Kuja‐Halkola Ralf2,Lichtenstein Paul2,Larsson Henrik23,Faraone Stephen V.14

Affiliation:

1. Department of Psychiatry and Behavioral Sciences SUNY Upstate Medical University Syracuse NY USA

2. Department of Medical Epidemiology and Biostatistics Karolinska Institutet Stockholm Sweden

3. School of Medical Sciences Örebro University Örebro Sweden

4. Department of Neuroscience and Physiology SUNY Upstate Medical University Syracuse NY USA

Funder

Vetenskapsrådet

Hjärnfonden

Publisher

Wiley

Subject

Psychiatry and Mental health,Developmental and Educational Psychology,Pediatrics, Perinatology, and Child Health

Reference61 articles.

1. Predicting Suicidal Behavior From Longitudinal Electronic Health Records

2. Childhood socioeconomic status and longitudinal patterns of alcohol problems: Variation across etiological pathways in genetic risk

3. Bergstra J. Yamins D. &Cox D. D.(2013).Making a Science of Model Search: Hyperparameter Optimizationin Hundreds of Dimensions for Vision Architectures. Paper presented at the 30th International Conference on Machine Learning (ICML 2013) Atlanta Gerorgia.

4. Risk Prediction Models in Psychiatry

5. Young adult outcome of attention deficit hyperactivity disorder: a controlled 10-year follow-up study

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