Commentary to “Translational machine learning for child and adolescent psychiatry”

Abstract

In this commentary on ‘Translational Machine Learning for Child and Adolescent Psychiatry,’ by Dwyer and Koutsouleris, we summarize some of the main points made by the authors, which highlight the importance of emerging applications of machine learning for psychiatric disorders in youth but also emphasize principles of good practice. We also offer complementary insights regarding large‐scale training, harmonization, and the ability of these artificial intelligence models to adapt to new datasets, which is critical for their stability across imaging centers, and hence for their widespread clinical adoption.

Editorial: The times they are a‐changin’: paradigm shifts in child and adolescent psychology and psychiatry

“…Finally, Dwyer & Koutsouleris (2022) illustrate the potential of machine learning methods that build on dimensional data across multiple levels of analysis to optimize predictions about prognosis and treatment. In their commentary, Davatzikos & Satterthwaite (2022) observe that these methods also have the potential to reduce diagnostic heterogeneity.…”

Erratum for Commentary to “Translational machine learning for child and adolescent psychiatry” by Davatzikos and Satterthwaite (2022)

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In Davatzikos and Satterthwaite (2022), in-text and reference details for Dwyer and Koutsouleris (2022) were missing. This has been added in the article.

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Erratum for ‘Editorial: The times they are a‐changin': paradigm shifts in child and adolescent psychology and psychiatry’ by Jaffee (2022)

“…In Jaffee (2022), in‐text citation and reference details for Anderson, Newlove‐Delgado, and Ford (2022), Astle, Holmes, Kievit, and Gathercole (2022), Cabrera (2022), Chronis‐Tuscano (2022), Davatzikos and Satterthwaite (2022), Dwyer and Koutsouleris (2022), Hinshaw, Nguyen, O’Grady, and Rosenthal (2022), Lansford (2022), Pellicano and den Houting (2022), Pacheco et al. (2022) and Tuomainen (2022) were missing.…”