Use of Artificial Intelligence-Based Software as Medical Devices for Chest Radiography: A Position Paper from the Korean Society of Thoracic Radiology

Korean J Radiol. 2021 Nov;22(11):1743-1748. doi: 10.3348/kjr.2021.0544. Epub 2021 Sep 13.

Eui Jin Hwang^{1

2}, Jin Mo Goo^{1

2

3}, Soon Ho Yoon^{1

2

4}, Kyongmin Sarah Beck⁵, Joon Beom Seo⁶, Byoung Wook Choi⁷, Myung Jin Chung⁸, Chang Min Park^{1

2}, Kwang Nam Jin⁹, Sang Min Lee⁶

¹ Department of Radiology, Seoul National University Hospital, Seoul, Korea.
² Department of Radiology and Institution of Radiation Medicine, Seoul National University College of Medicine, Seoul, Korea.
³ Cancer Research Institute, Seoul National University, Seoul, Korea. jmgoo@plaza.snu.ac.kr.
⁴ Department of Radiology, UMass Memorial Medical Center, Worcester, MA, USA.
⁵ Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
⁶ Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
⁷ Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
⁸ Department of Radiology and Medical AI Research Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
⁹ Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea.

No abstract available

Keywords: Artificial intelligence; Chest radiography; Computer-aided detection; Deep learning.

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