Clinical Research Directory

Cl-Pharm-IBS-ML-2026

Sponsor: Tanta University

Summary

The purpose of this study is to identify distinct subgroups (phenotypes) of Irritable Bowel Syndrome (IBS) patients. While traditional IBS classification relies mainly on bowel habits, this research uses a multidimensional questionnaire to capture clinical symptoms, psychological factors, diet triggers, sleep quality, and digital behaviors. By applying advanced machine learning algorithms to these patient-reported outcomes, the study aims to uncover hidden patterns that can help customize future treatments and improve patient care.

Official title: Machine Learning-Based Phenotyping of IBS Patients Using Multidimensional Patient-Reported Outcomes

Key Details

Conditions

Interventions