AI in Esophageal Motility Disorders: Systematic Review of High-Resolution Manometry Studies.

ABSTRACT:

Background

High-resolution esophageal manometry (HRM) is essential for diagnosing esophageal motility disorders, affecting 10%-15% of patients with dysphagia. Current interpretation via the Chicago Classification remains challenging, with interobserver variability reaching 30%-40% even among experts. Artificial intelligence (AI) has emerged as a transformative tool to automate HRM interpretation.

Objective

We aimed to evaluate current AI HRM applications and assess diagnostic accuracy, methodological approaches, clinical validation, implementation barriers, and real-world implications for gastroenterology practice.

Methods

We searched PubMed/MEDLINE, Embase, Cochrane Library, and Web of Science through November 2025, for studies using AI or machine learning to interpr

SUBMITTER: Gong EJ 

PROVIDER: S-EPMC12699254 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature