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Authors
Castro-Zunti, Riel https://orcid.org/0000-0002-3977-8958
Park, Eun Hae https://orcid.org/0000-0001-9901-6333
Satsangi, Amol https://orcid.org/0009-0005-8611-5654
Choi, Younhee
Jin, Gong Yong https://orcid.org/0000-0002-1426-554X
Chae, Hee Suk https://orcid.org/0000-0001-7297-534X
Ko, Seok-Bum https://orcid.org/0000-0002-9287-317X
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Article History
Received: 24 October 2024
Accepted: 23 December 2024
First Online: 29 October 2025
Declarations
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: The authors declared that they have no conflicts of interest to this work.
: This research has not, to the best of the researchers’ knowledge, violated the guidelines/principals of the Declaration of Helsinki and its amendments.The Institutional Review Board of Jeonbuk National University Hospital approved this retrospective study and waived the requirement for written informed consent. The research ethics board at the University of Saskatchewan approved the retrospective study into the development of AS diagnostic systems using deep learning.
: The Institutional Review Board of Jeonbuk National University Hospital waived the requirement for informed consent. All image data underwent anonymization. Given current technologies, a patient’s identity cannot be determined from their published images/data herein this article.
