Machine learning in mental health: a sco** review of methods and applications

ABR Shatte, DM Hutchinson, SJ Teague - Psychological medicine, 2019 - cambridge.org
BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …

Toward precision medicine in ADHD

J Buitelaar, S Bölte, D Brandeis, A Caye… - Frontiers in behavioral …, 2022 - frontiersin.org
Attention-Deficit Hyperactivity Disorder (ADHD) is a complex and heterogeneous
neurodevelopmental condition for which curative treatments are lacking. Whilst …

Individualized prediction models in ADHD: a systematic review and meta-regression

G Salazar de Pablo, R Iniesta, A Bellato, A Caye… - Molecular …, 2024 - nature.com
There have been increasing efforts to develop prediction models supporting personalised
detection, prediction, or treatment of ADHD. We overviewed the current status of prediction …

Annual Research Review: Translational machine learning for child and adolescent psychiatry

D Dwyer, N Koutsouleris - Journal of Child Psychology and …, 2022 - Wiley Online Library
Children and adolescents could benefit from the use of predictive tools that facilitate
personalized diagnoses, prognoses, and treatment selection. Such tools have not yet been …

[HTML][HTML] Effectiveness of mental health care by using machine learning on manufacturing worker

J Lim, S Lee, J Noh, W Lee, PC Su… - International Journal of …, 2023 - ijpem-st.org
Despite the remarkable advancements in technology that have accelerated and enhanced
manufacturing processes, it remains crucial to acknowledge the ongoing significance of …

[HTML][HTML] Predicting efficacy of viloxazine extended-release treatment in adults with ADHD using an early change in ADHD symptoms: machine learning post hoc …

SV Faraone, R Gomeni, JT Hull, SA Chaturvedi… - Psychiatry …, 2022 - Elsevier
Early response to viloxazine extended-release (viloxazine ER, Qelbree®) treatment
predicted efficacy outcome in pediatric subjects with attention-deficit/hyperactivity disorder …

[HTML][HTML] Early response to SPN-812 (viloxazine extended-release) can predict efficacy outcome in pediatric subjects with ADHD: a machine learning post-hoc analysis …

SV Faraone, R Gomeni, JT Hull, GD Busse, Z Melyan… - Psychiatry …, 2021 - Elsevier
Abstract Machine learning (ML) was used to determine whether early response can predict
efficacy outcome in pediatric subjects with ADHD treated with SPN-812. We used data from …

Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques

S Saggu, H Daneshvar, R Samavi, P Pires… - BMC Medical Informatics …, 2024 - Springer
Abstract Background The proportion of Canadian youth seeking mental health support from
an emergency department (ED) has risen in recent years. As EDs typically address urgent …

Neurobiological support to the diagnosis of ADHD in stimulant‐naïve adults: Pattern recognition analyses of MRI data

TM Chaim‐Avancini, J Doshi, MV Zanetti… - Acta Psychiatrica …, 2017 - Wiley Online Library
Objective In adulthood, the diagnosis of attention‐deficit/hyperactivity disorder (ADHD) has
been subject of recent controversy. We searched for a neuroanatomical signature …

Pharmacogenetics of methylphenidate in childhood attention-deficit/hyperactivity disorder: long-term effects

CI Gomez-Sanchez, JJ Carballo, R Riveiro-Alvarez… - Scientific reports, 2017 - nature.com
Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in
which a significant proportion of patients do not respond to treatment. The objective of this …