Brain morphometric features predict depression symptom phenotypes in late-life depression using a deep learning model

Brain morphometric features predict depression symptom phenotypes in late-life depression using a deep learning model

ObjectivesOur objective was to use deep learning models to identify underlying brain regions associated with depression symptom phenotypes in late-life depression (LLD).ParticipantsDiagnosed with LLD (N = 116) and enrolled in a prospective treatment study.DesignCross-sectional.MeasurementsStructural...

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Bibliographic Details
Main Authors: Bing Cao, Erkun Yang, Lihong Wang, Zhanhao Mo, David C. Steffens, Han Zhang, Mingxia Liu, Guy G. Potter
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-07-01
Series:Frontiers in Neuroscience
Subjects:
cross-sectional late-life depression
deep learning
factor score prediction
cognitive impairment
Alzheimer's disease
structural MRI Frontiers
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1209906/full

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https://www.frontiersin.org/articles/10.3389/fnins.2023.1209906/full

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