Functional and structural MRI based obsessive-compulsive disorder diagnosis using machine learning methods.

ABSTRACT:

Background

The success of neuroimaging in revealing neural correlates of obsessive-compulsive disorder (OCD) has raised hopes of using magnetic resonance imaging (MRI) indices to discriminate patients with OCD and the healthy. The aim of this study was to explore MRI based OCD diagnosis using machine learning methods.

Methods

Fifty patients with OCD and fifty healthy subjects were allocated into training and testing set by eight to two. Functional MRI (fMRI) indices, including amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), degree of centrality (DC), and structural MRI (sMRI) indices, including volume of gray matter, cortical thickness and sulcal depth, were extracted in each brain region as features. The features were red

SUBMITTER: Huang FF 

PROVIDER: S-EPMC10617132 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature