Fourth paper published in Radiology
Authors
Eui Jin Hwang¹, Jong Hyuk Lee¹, Woo Hyeon Lim¹, Won Gi Jeong², Wonju Hong³, Jongsoo Park⁴, Seung-Jin Yoo⁵, Hyungjin Kim¹,⁶
¹ Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea
² Department of Radiology, Chonnam National University Hwasun Hospital and Chonnam National University Medical School, Hwasun, Republic of Korea
³ Department of Radiology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
⁴ Department of Radiology, Yeungnam University Medical Center and Yeungnam University College of Medicine, Daegu, Republic of Korea
⁵ Department of Radiology, Hanyang University Medical Center and Hanyang University College of Medicine, Seoul, Republic of Korea
⁶ Soombit.ai, Seongnam, Republic of Korea
Abstract
When evaluated by a panel of expert thoracic radiologists, artificial intelligence–generated chest radiograph reports showed an overall clinical acceptance rate of 87.6%, with acceptance rates differing by clinical context.
Published in Radiology, 2025
https://doi.org/10.1148/radiol.250568