Deep Learning Analysis to Automatically Detect the Presence of Penetration or Aspiration in Videofluoroscopic Swallowing Study-Reference-Cited by-同舟云学术

Deep Learning Analysis to Automatically Detect the Presence of Penetration or Aspiration in Videofluoroscopic Swallowing Study

Author:

Kim Jeoung Kun¹^ORCID,Choo Yoo Jin²^ORCID,Choi Gyu Sang³^ORCID,Shin Hyunkwang³^ORCID,Chang Min Cheol²^ORCID,Park Donghwi⁴^ORCID

Affiliation:

1. Department of Business Administration, School of Business, Yeungnam University, Gyeongsan, Korea.

2. Department of Rehabilitation Medicine, College of Medicine, Yeungnam University, Daegu, Korea.

3. Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, Korea.

4. Department of Physical Medicine and Rehabilitation, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea.

Funder

National Research Foundation of Korea

Yeungnam University

Publisher

Korean Academy of Medical Sciences

Subject

General Medicine

Link

Reference26 articles.

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