Re-investigation of functional gastrointestinal disorders utilizing a machine learning approach.

ABSTRACT:

Background

Functional gastrointestinal disorders (FGIDs), as a group of syndromes with no identified structural or pathophysiological biomarkers, are currently classified by Rome criteria based on gastrointestinal symptoms (GI). However, the high overlap among FGIDs in patients makes treatment and identifying underlying mechanisms challenging. Furthermore, disregarding psychological factors in the current classification, despite their approved relationship with GI symptoms, underlines the necessity of more investigation into grouping FGID patients. We aimed to provide more homogenous and well-separated clusters based on both GI and psychological characteristics for patients with FGIDs using an unsupervised machine learning algorithm.

Methods

Based on a cross-sectional study,

SUBMITTER: Mousavi E 

PROVIDER: S-EPMC10463372 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature