Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

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作者： Shengchuan,Feng ^[1] ; Ran,Zhang ^[2] ; Wenxiu,Zhang ^[3] ; Yuqiong,Yang ^[4] ; Aiqi,Song ^[5] ; Jiawei,Chen ^[6] ; Fengyan,Wang ^[4] ; Jiaxuan,Xu ^[4] ; Cuixia,Liang ^[2] ; Xiaoyun,Liang ^[3] ; Rongchang,Chen ^[4] ; Zhenyu,Liang ^[4]

作者单位： State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Department of Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China, fengsc2022@163.com. ^[1] Neusoft Medical Systems Co., Ltd., Shenyang, China. ^[2] Institute of Research and Clinical Innovations, Neusoft Medical Systems Co., Ltd., Shanghai, China. ^[3] State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Department of Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China. ^[4] Nanshan School, Guangzhou Medical University, Guangzhou, China. ^[5] First Clinical School, Guangzhou Medical University, Guangzhou, China. ^[6]

关键词 Acute exacerbation Chronic obstructive pulmonary disease High-resolution computed tomography Quantitative computed tomography VGG-16