Support vector machine classification of irritable bowel syndrome patients based on whole-brain resting-state functional connectivity features.

ABSTRACT:

Background

Irritable bowel syndrome (IBS) is a disorder characterized by signaling dysregulation between the brain and gut, leading to gastrointestinal dysfunction. Symptoms such as abdominal pain and constipation can manifest periodically or persistently, and negative emotions may exacerbate the symptoms. Previous studies have shown that the pathogenesis of IBS is closely related to the brain-gut axis and brain function, but there are still difficulties in disease diagnosis. Therefore, this study applied a machine-learning approach based on resting-state functional magnetic resonance imaging (rs-fMRI) whole-brain functional connectivity (FC) to distinguish IBS patients from healthy controls (HCs).

Methods

A total of 176 subjects, comprising 88 consecutive patients with IBS

SUBMITTER: Xie L 

PROVIDER: S-EPMC11485364 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature