Neuroanatomical markers of psychotic experiences in adolescents: A machine-learning approach in a longitudinal population-based sample

Neuroanatomical markers of psychotic experiences in adolescents: A machine-learning approach in a longitudinal population-based sample

It is important to identify accurate markers of psychiatric illness to aid early prediction of disease course. Subclinical psychotic experiences (PEs) are important risk factors for later mental ill-health and suicidal behaviour. This study used machine learning to investigate neuroanatomical marker...

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Bibliographic Details
Main Authors: Joanne P.M. Kenney, Laura Milena Rueda-Delgado, Erik O. Hanlon, Lee Jollans, Ian Kelleher, Colm Healy, Niamh Dooley, Conor McCandless, Thomas Frodl, Alexander Leemans, Catherine Lebel, Robert Whelan, Mary Cannon
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:NeuroImage: Clinical
Subjects:
Machine learning
Psychotic experiences
Adolescents
Neuroanatomy
Structural MRI
Diffusion MRI
Online Access:http://www.sciencedirect.com/science/article/pii/S2213158222000481

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http://www.sciencedirect.com/science/article/pii/S2213158222000481

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