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

Background: Children with attention‐deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at‐risk youth would help allocate scarce resources for prevention programs. Methods: Psychiatric and somatic diagnoses, family history of these disor...

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Detalles Bibliográficos

Publicado en:	Journal of Child Psychology & Psychiatry Vol. 61; no. 12; pp. 1370 - 1380
Autores principales:	Zhang‐James, Yanli, Chen, Qi, Kuja‐Halkola, Ralf, Lichtenstein, Paul, Larsson, Henrik, Faraone, Stephen V.
Formato:	Artículo
Publicado:	Wiley-Blackwell Dec2020
Materias:	Substance abuse diagnosis Attention-deficit hyperactivity disorder Calibration Confidence intervals Reporting of diseases Machine learning Artificial neural networks Risk assessment Time Comorbidity Prediction models Receiver operating characteristic curves Random forest algorithms
Acceso en línea:	Ver este registro en EBSCOhost