首页> Journal of the American Medical Informatics Association : JAMIA> Accounting for data variability in multi-institutional distributed deep learning for medical imaging.

Accounting for data variability in multi-institutional distributed deep learning for medical imaging.

导出 OA

翻译打印收藏纠错

第一作者： Niranjan,Balachandar

第一单位： Laboratory of Quantitative Imaging and Artificial Intelligence, Department of Radiology and Biomedical Data Science, Stanford University, Stanford, CA, USA.

作者： Niranjan,Balachandar ^[1] ; Ken,Chang ^[2] ; Jayashree,Kalpathy-Cramer ^[3] ; Daniel L,Rubin ^[1]

作者单位： Laboratory of Quantitative Imaging and Artificial Intelligence, Department of Radiology and Biomedical Data Science, Stanford University, Stanford, CA, USA. ^[1] Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA. ^[2] Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.;MGH and BWH Center for Clinical Data Science, Massachusetts General Hospital, Boston, MA, USA. ^[3]

关键词 deep learning distributed learning federated learning medical imaging, transfer learning

医学主题词计算机通信网络(Computer Communication Networks);糖尿病视网膜病变(Diabetic Retinopathy);诊断显像(Diagnostic Imaging);人类(Humans);模式识别, 自动(Pattern Recognition, Automated);放射摄影术, 胸部(Radiography, Thoracic)

DOI 10.1093/jamia/ocaa017

PMID 32196092

发布时间 2024-03-31

基金项目

U24 CA180918/CA/NCI NIH HHS/United States U01 CA242879/CA/NCI NIH HHS/United States U24 CA180927/CA/NCI NIH HHS/United States T32 EB001680/EB/NIBIB NIH HHS/United States F30 CA239407/CA/NCI NIH HHS/United States P41 EB015896/EB/NIBIB NIH HHS/United States U01 CA154601/CA/NCI NIH HHS/United States

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交