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Authors
Kang, Yusuhn https://orcid.org/0000-0003-1838-2564
Choi, Dongjun
Lee, Kyong Joon
Oh, Joo Han
Kim, Bo Ram
Ahn, Joong Mo
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Funding
Funding for this research was provided by:
National Research Foundation of Korea (NRF-2019R1F1A1060126)
SNUBH Research Fund (14-2020-038)
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Article History
Received: 23 December 2020
Revised: 6 April 2021
Accepted: 30 April 2021
First Online: 20 May 2021
Declarations
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: The scientific guarantor of this publication is Yusuhn Kang.
: The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
: One of the authors (Dongjun Choi) has significant statistical expertise.
: Written informed consent was waived by the Institutional Review Board.
: Institutional Review Board approval was obtained.
: Some study subjects or cohorts have been previously reported in Kim Y, Choi D, Lee KJ et al (2020) Ruling out rotator cuff tear in shoulder radiograph series using deep learning: redefining the role of conventional radiograph. Eur Radiol 30:2843-2852.
: • Retrospective• Experimental• Performed at one institution
