Impact of Exposure Parameters on Deep Learning Models in Chest Radiography and Implications for Deployment.

求助中 20 由朱泽均发布于 2026/8/26 8:36:54

DOI:10.1148/ryai.250731
作者：Han-Jay Shu,?Shun-Ting Chang,?Rodrigo Rosa Gameiro,?Judy Wawira Gichoya,?Leo Anthony Celi,?Po-Chih Kuo
文献类型：期刊论文
补充材料：只需要正文
文献链接：https://doi.org/10.1148/ryai.250731

其它数据库

Abstract：Purpose To investigate whether deep learning models trained on chest radiographs rely on radiographic exposure parameters as shortcut features and to quantify the resulting biases under cont

应助信息

等您来应助

上传文件

1天前

Book学术机器人

2026/8/26 8:36:54 未找到该文献，机器人已退出，请等待人工下载

2026/8/26 8:36:54 Book学术AI机器人收到请求，开始寻找文献

2026/8/26 8:36:54 已向机器人发送请求

1天前

朱泽均发布求助

上一个求助:其它数据库Naturally Fractured Carbonate Reservoir Characterization: A Case Study of a Mature High-Pour Point Oil Field in Hungary 下一个求助:American Chemical Society (ACS)Discovery of Highly Efficacious CRBN-Based KRAS Degraders Targeting Cancers with KRAS G12D and G12V Mutations