Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software.

Abstract

Authors

• Hee Jeong Kim
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea.
• Woo Jung Choi
  Department of Radiology, Hanyang University Hospital, Seoul, South Korea; Department of Radiology, University of Ulsan, Asan Medical Center, Seoul, South Korea.
• Hye Yun Gwon
  Department of Radiology, Hallym University Sacred Heart Hospital, 22, Gwanpyeong-Ro 170-Gil, Dongan-Gu, Anyang-Si, Gyeonggi-Do, 14068, South Korea.
• Seo Jin Jang
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea.
• Eun Young Chae
• Hee Jung Shin
  Department of Radiology, Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Republic of Korea.
• Joo Hee Cha
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea.
• Hak Hee Kim

Keywords

External Resources