Fifth paper published in Radiology
Authors
Hyungjin Kim¹˒², Jong Eun Lee³, Kum Ju Chae⁴, Jooae Choe³, Jung Hee Hong⁵, Kwang Nam Jin⁶, Hyo-jae Lee⁷, Yun-Hyeon Kim⁸, Anna J. Podolanczuk⁹, Christopher J. Ryerson¹⁰, Yeon Joo Jeong¹¹, Soon Ho Yoon¹
¹ Seoul National University Hospital and Seoul National University College of Medicine, Seoul, South Korea
² Soombit.AI, Seongnam, South Korea
³ University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
⁴ Jeonbuk National University–Jeonbuk National University Hospital, Jeonju, South Korea
⁵ Keimyung University Dongsan Medical Center, Daegu, South Korea
⁶ Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, South Korea
⁷ Chonnam National University Hwasun Hospital, Hwasun, South Korea
⁸ Chonnam National University Hospital, Gwangju, South Korea
⁹ Weill Cornell Medical College, New York, USA
¹⁰ University of British Columbia and St. Paul's Hospital, Vancouver, Canada
¹¹ Pusan National University Hospital, Busan, South Korea
Abstract
Background: Interstitial lung abnormalities (ILA) on chest CT are receiving growing attention given their association with progression to interstitial lung disease. Radiography's role in ILA detection is not well described.
Objective: To evaluate the diagnostic performance of radiologists and an artificial intelligence (AI) model in detecting ILA on chest radiographs using CT as the reference.
Published in American Journal of Roentgenology
https://www.ajronline.org/doi/10.2214/AJR.26.34686