TY - T1的开发和验证的学习算法检测10常见异常胸片JF -欧洲呼吸杂志》乔和J - 10.1183/13993003.03061 -2020欧元SP - 2003061 AU -南,Ju帮派AU -金,Minchul盟——公园、Jongchan AU -黄,行金盟- Lee Jong Hyuk AU -香港,荣格庆熙盟——咕金墨盟,公园,Chang分钟Y1 - 2020/01/01 UR - //www.qdcxjkg.com/content/early/2020/11/05/13993003.03061 - 2020. -抽象N2 -我们旨在开发一个深度学习算法检测10常见异常(DLAD-10)胸片和评估其影响诊断的准确性,及时性的报告和工作流功效。DLAD-10使用来自108 053名患者的146 717张x线片进行训练，使用基于resnet34的神经网络对10种常见的影像学异常(气胸、纵隔增宽、气腹、结节/肿块、实变、胸腔积液、线性不张、纤维化、钙化和心脏肿大)的病变特异性通道进行训练。对于外部验证，DLAD-10在同一天ct确认的数据集(正常:异常，53:147)和一个开源数据集(PadChest;正常:不正常，339:334)与三位放射科医生进行了比较。对另一个数据集进行了单独的模拟阅读测试，该数据集根据急诊科的真实疾病流行情况进行了调整，包括4个危重病例、52个紧急病例和146个非紧急病例。六名放射科医生参加了有或没有DLAD-10的模拟阅读会议。在ct确认数据集中，DLAD-10的接受者工作特征曲线(auroc)下面积为0.895-1.00，在PadChest数据集中为0.913-0.997。DLAD-10正确分类的严重异常(95.0%[57/60])明显多于联合放射科医师(84.4% [152/180];p = 0.01)。在对急诊科患者的模拟阅读测试中，合并阅读器明显发现了更严重的问题(70.8% [17/24]vs 29.2% [7/24]; p=0.006) and urgent (82.7% [258/312] versus 78.2% [244/312]; p=0.04) abnormalities when aided by DLAD-10. DLAD-10 assistance shortened the mean time-to-report critical and urgent radiographs (640.5±466.3 versus 3371.0±1352.5 s and 1840.3±1141.1 versus 2127.1±1468.2, respectively; p-values<0.01) and reduced the mean interpretation time (20.5±22.8 versus 23.5±23.7 s; p<0.001).DLAD-10 showed excellent performance, improving radiologists' performance and shortening the reporting time for critical and urgent cases.FootnotesThis manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article.Conflict of interest: Dr. NAM reports grants from National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (MSIT) (grant number: NRF-2018R1A5A1060031), grants from Seoul National University Hospital Research Fund (grant number: 03-2019-0190), during the conduct of the study.Conflict of interest: Dr. Kim reports other from Employee of Lunit Incorporated, during the conduct of the study.Conflict of interest: Dr. Park reports grants from National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (MSIT) (grant number: NRF-2018R1A5A1060031), grants from Seoul National University Hospital Research Fund (grant number: 03-2019-0190), during the conduct of the study.Conflict of interest: Dr. Hwang has nothing to disclose.Conflict of interest: Dr. Lee has nothing to disclose.Conflict of interest: Dr. Hong has nothing to disclose.Conflict of interest: Dr. Goo has nothing to disclose.Conflict of interest: Dr. Park reports grants from National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (MSIT) (grant number: NRF-2018R1A5A1060031), grants from Seoul National University Hospital Research Fund (grant number: 03-2019-0190), during the conduct of the study. ER -