Application of deep learning technology for temporal analysis of videofluoroscopic swallowing studies

Temporal parameters during swallowing are analyzed for objective and quantitative evaluation of videofluoroscopic swallowing studies (VFSS). Manual analysis by clinicians is time-consuming, complicated and prone to human error during interpretation; therefore, automated analysis using deep learning...

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Bibliographic Details
Published in:	Scientific reports Vol. 13; no. 1; pp. 17522 - 12
Main Authors:	Jeong, Seong Yun, Kim, Jeong Min, Park, Ji Eun, Baek, Seung Jun, Yang, Seung Nam
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 16.10.2023 Nature Publishing Group Nature Portfolio
Subjects:	639/166 692/308 Deep Learning Deglutition - physiology Deglutition Disorders - diagnostic imaging Deglutition Disorders - etiology Esophageal sphincter Esophageal Sphincter, Upper Fluoroscopy - methods Humanities and Social Sciences Humans multidisciplinary Pharynx Science Science (multidisciplinary) Sphincter Swallowing
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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