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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Scientific reports Jg. 13; H. 1; S. 17522 - 12
Hauptverfasser:	Jeong, Seong Yun, Kim, Jeong Min, Park, Ji Eun, Baek, Seung Jun, Yang, Seung Nam
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 16.10.2023 Nature Publishing Group Nature Portfolio
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!