한빛사논문
- 조회302
Joon-Hyop Leea, Young Jun Chaib,c,*
aDepartment of Surgery, Gachon University College of Medicine, Gil Medical Center, Incheon, South Korea
bDepartment of Surgery, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul 07061, South Korea
cTransdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
*Corresponding author.
Abstract
In The Lancet Digital Health, Sui Peng and colleagues, showed the ability of a deep-learning model (ThyNet) to improve radiologists' diagnostic performance when determining the nature of a thyroid nodule. Unlike previous studies that compared the accuracy of humans and artificial intelligence (AI) performance, this study is important because it shows that the future of diagnostics is cooperation and synergy between humans and AI, rather than exclusivity and usurpation. Radiological diagnosis of thyroid nodules can be difficult in many situations, even with the American College of Rheumatology Thyroid Imaging Reporting and Data System, and if ThyNet can augment radiologists' diagnostic capabilities in general settings, it would be a breakthrough in managing thyroid nodules. However, there are issues that should be addressed.
논문정보
- Correspondence
- 2021년 07월 (BRIC 등록일 2021-08-23)
- 국내 연구진
- 의약학 > 응용의학
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