‘Can we diagnose mental disorders in children? A large-scale assessment of machine learning on structural neuroimaging of 6916 children in the adolescent brain cognitive development study’
Open Access paper from JCPP Advances
Using data from 6916 children aged 9–10 in the multicenter Adolescent Brain Cognitive Development study, we extracted 136 regional volume and thickness measures from structural magnetic resonance images to rigorously evaluate the capabilities of machine learning to predict 10 different psychiatric disorders: major depressive disorder, bipolar disorder (BD), psychotic symptoms, attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, post-traumatic stress disorder, obsessive-compulsive disorder, generalized anxiety disorder, and social anxiety disorder. For each disorder, we performed cross-validation and assessed whether models discovered a true pattern in the data via permutation testing.
Authors: Richard Gaus, Sebastian Pölsterl, Ellen Greimel, Gerd Schulte-Körne, Christian Wachinger
Richard Gaus and Sebastian Pölsterl are contributed equally to this work.
First published: 28 June 2023
https://doi.org/10.1002/jcv2.12184
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