Applications of Artificial Intelligence in Instrumental Swallowing Assessment: A Scoping Review of VFSS and FEES Research

Author: Priyaraagavi Dhanaraj

Field of Study: Speech and Language Pathology

Faculty Mentors: Sundeep Venkatesan

Easel: 96

Timeslot: Afternoon

Abstract: Dysphagia affects millions of adults worldwide and affects the quality of life and swallowing function. Video Fluoroscopic Swallowing Study (VFSS) and Fiberoptic Endoscopic Evaluation of Swallowing (FEES) are widely regarded as the gold standard instrumental assessments for diagnosing swallowing impairment. However, their interpretation is often time-consuming and subjective to inter-rater variability. Artificial Intelligence (AI), particularly deep learning, has emerged as a transformative tool to automate analysis, improve diagnostic accuracy, and provide objective quantification of swallowing biomechanics. This scoping review aims to map the current landscape of AI applications in VFSS and FEES, identifying the primary technological trends, clinical targets, and existing gaps in the literature. A comprehensive search was conducted across PubMed, Web of Science, Embase, IEEE Xplore and MedRxiv. Data analysis is currently underway and aims to identify key applications of AI in instrumental analysis and potential significance in the interpretation of VFSS and FEES.