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Manometry

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Deep learning-based artificial intelligence model for identifying swallow types in esophageal high-resolution manometry.

Neurogastroenterology and motility
BACKGROUND: This study aimed to build and evaluate a deep learning, artificial intelligence (AI) model to automatically classify swallow types based on raw data from esophageal high-resolution manometry (HRM).

A multi-stage machine learning model for diagnosis of esophageal manometry.

Artificial intelligence in medicine
High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its manual interpretation and classification, including evaluation of swallow-level outcomes and then derivation of a study-level diagnosis based...

Video-Based Deep Learning to Detect Dyssynergic Defecation with 3D High-Definition Anorectal Manometry.

Digestive diseases and sciences
BACKGROUND: We developed a deep learning algorithm to evaluate defecatory patterns to identify dyssynergic defecation using 3-dimensional high definition anal manometry (3D-HDAM).

Artificial Intelligence and Anorectal Manometry: Automatic Detection and Differentiation of Anorectal Motility Patterns-A Proof-of-Concept Study.

Clinical and translational gastroenterology
INTRODUCTION: Anorectal manometry (ARM) is the gold standard for the evaluation of anorectal functional disorders, prevalent in the population. Nevertheless, the accessibility to this examination is limited, and the complexity of data analysis and re...

Achalasia phenotypes and prediction of peroral endoscopic myotomy outcomes using machine learning.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: High-resolution manometry (HRM) and esophagography are used for achalasia diagnosis; however, achalasia phenotypes combining esophageal motility and morphology are unknown. Moreover, predicting treatment outcomes of peroral endoscopic myo...

Current Status and Role of Artificial Intelligence in Anorectal Diseases and Pelvic Floor Disorders.

JSLS : Journal of the Society of Laparoendoscopic Surgeons
BACKGROUND: Anorectal diseases and pelvic floor disorders are prevalent among the general population. Patients may present with overlapping symptoms, delaying diagnosis, and lowering quality of life. Treating physicians encounter numerous challenges ...

A new methodology for determining the central pressure waveform from peripheral measurement using Fourier-based machine learning.

Artificial intelligence in medicine
Radial applanation tonometry is a well-established technique for hemodynamic monitoring and is becoming popular in affordable non-invasive wearable healthcare electronics. To assess the central aortic pressure using radial-based measurements, there i...

Gemini-Assisted Deep Learning Classification Model for Automated Diagnosis of High-Resolution Esophageal Manometry Images.

Medicina (Kaunas, Lithuania)
To develop a deep learning model for esophageal motility disorder diagnosis using high-resolution manometry images with the aid of Gemini. Gemini assisted in developing this model by aiding in code writing, preprocessing, model optimization, and tr...

Comparison of measurement of integrated relaxation pressure by esophageal manometry with analysis of swallowing sounds with artificial intelligence in patients with achalasia.

Neurogastroenterology and motility
BACKGROUND: Esophageal motility disorders are mainly evaluated with high-resolution manometry (HRM) which is a time-consuming and uncomfortable procedure with potential adverse events. Acoustic characterization of the swallowing has the potential to ...

Artificial intelligence as a transforming factor in motility disorders-automatic detection of motility patterns in high-resolution anorectal manometry.

Scientific reports
High-resolution anorectal manometry (HR-ARM) is the gold standard for anorectal functional disorders' evaluation, despite being limited by its accessibility and complex data analysis. The London Protocol and Classification were developed to standardi...