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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Detalles Bibliográficos
Autores principales: Jeong, Seong Yun, Kim, Jeong Min, Park, Ji Eun, Baek, Seung Jun, Yang, Seung Nam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10579219/
https://www.ncbi.nlm.nih.gov/pubmed/37845272
http://dx.doi.org/10.1038/s41598-023-44802-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10579219/
https://www.ncbi.nlm.nih.gov/pubmed/37845272
http://dx.doi.org/10.1038/s41598-023-44802-3

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