Cargando…
Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches
BACKGROUND: There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographic, clinical questionnaire, environmental, neuropsy...
Autores principales: | Kim, Jae-Won, Sharma, Vinod, Ryan, Neal D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756719/ https://www.ncbi.nlm.nih.gov/pubmed/25964505 http://dx.doi.org/10.1093/ijnp/pyv052 |
Ejemplares similares
-
Prediction of sleep side effects following methylphenidate treatment in ADHD youth
por: Yoo, Jae Hyun, et al.
Publicado: (2019) -
ADHD, Methylphenidate, and Childhood Epilepsy
por: Sharma, Rahul, et al.
Publicado: (2016) -
Regional brain volume predicts response to methylphenidate treatment in individuals with ADHD
por: Chang, Jung-Chi, et al.
Publicado: (2021) -
The Risk of Methylphenidate Pharmacotherapy for Adults with ADHD
por: Bieś, Rafał, et al.
Publicado: (2023) -
Correction to: Regional brain volume predicts response to methylphenidate treatment in individuals with ADHD
por: Chang, Jung-Chi, et al.
Publicado: (2021)