Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data

Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data

Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and reduce both individual and societal costs. This study aimed to develop predictive models for depression in young adults using machine learning (ML) techniques and longitudinal data from the Beck Depre...

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Bibliographic Details
Main Authors: Ailing Zhang, Haobo Zhang
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:NeuroImage
Subjects:
Machine learning
Depression
Predictive modeling
Magnetic resonance imaging (mri)
Support vector machine (svm)
Random forest
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811925002885
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