New Technologies for Detecting and Diagnosing Dysphagia: AI, Swallowing CT, and Respiratory Monitoring

Monday, May 18, 2026

2:30 PM - 3:30 PM PT

Location: 121 & 122

Ideal Audience:Administrators, Physicians, Researchers, Residents/Fellows

Course Director(s)

Yoko Inamoto, PhD

Dr
Fujita Health University

Speaker(s)

Byung-Mo Oh, MD

Professor
Seoul National University College of Medicine
EV

Eric Verin, MD

Head of Department
Normandie University

Moderator(s)

Marlis Gonzalez Fernandez, MD, PhD (she/her/hers)

Professor
Johns Hopkins University School of Medicine

Brief Session Description : This course showcases emerging technologies that sharpen dysphagia detection and diagnosis. We review AI pipelines for screening, automated MBS anomaly detection, voice-based risk flagging, and auto-report generation; demonstrate Swallowing CT for 3D/4D kinematic analysis and for validating conventional 2D MBS measures; and update respiratory monitoring for dysphagia associated with respiration disorders (e.g., COPD, OSA), including practical signal acquisition and interpretation. Attendees receive a one-page handout distilling key algorithms, device setups, safety notes, and “first-week” clinical workflows to accelerate adoption.

Session Objectives:

Describe AI applications for dysphagia screening, MBS abnormality detection, voice-based risk stratification, and automated reporting.

Interpret Swallowing CT kinematic findings and link them to physiology/pathophysiology; understand how CT can validate 2D MBS measures.

Apply respiratory monitoring concepts to dysphagia in respiration disorders (signal choice, thresholds, safety), and plan an integration pathway for routine clinics.
CanMEDS: Medical Expert. Health Advocate. Scholar.