Accessibility settings

This paper is in the following e-collection/theme issue:

Digital Health Reviews (3639) Clinical Information and Decision Making (3672) Decision Support for Health Professionals (2208) Machine Learning (3140) Gastroenterology and Hepatology (201) Artificial Intelligence (4718) Computer-Aided Diagnosis (416)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/85223, first published .
Man looking unenthusiastically at a forkful of salad

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

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

Authors of this article:

Eun Jeong Gong1, 2, 3 Author Orcid Image ;   Chang Seok Bang2, 3, 4 Author Orcid Image ;   Jae Jun Lee3, 5 Author Orcid Image ;   Gwang Ho Baik1, 2 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Geiger A, Wagner L, Rueckert D, Knoll A, Wilhelm D, Jell A. Multimodal graph-based classification of esophageal motility disorders. International Journal of Computer Assisted Radiology and Surgery 2026 View
  2. Guo Y, Zhao T, Zhang L, Liu Y, Liu K, Han B, Zhao Y, Shao J, Zhao L. Artificial intelligence in thyroid ultrasound: clinical applications and perspectives. Frontiers in Endocrinology 2026;17 View
  3. Robalino Gonzaga E, Madej J, Ahuja N. Artificial Intelligence for Diagnosis of Esophageal Manometry: A Narrative Review. Current Gastroenterology Reports 2026;28(1) View