Showing 21 - 29 results of 29 for search 'Ye County', query time: 0.06s Refine Results
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    Risk of All-Cause Mortality in Mild Chronic Obstructive Pulmonary Disease: Evidence From the NHANES III and 2007–2012 by Zou W, Ou J, Wu F, Xiao S, Deng Z, Li H, Wang Z, Tang G, Liu S, Ye D, Zhu D, Hu J, Ran P

    Published 2025-01-01
    “…Weifeng Zou,1,2,* Jie Ou,1,2,* Fan Wu,3,4,* Shan Xiao,5 Zhishan Deng,3 Haiqing Li,3 Zihui Wang,3 Gaoying Tang,3 Shuling Liu,1 Dong Ye,6 Dongshuang Zhu,2 Jinxing Hu,1 Pixin Ran3,4 1State Key Laboratory of Respiratory Disease, Guangzhou Chest Hospital, Guangzhou, People’s Republic of China; 2Department of Pulmonary and Critical Care Medicine, Shufu County People’s Hospital, Kashgar region, Xinjiang, People’s Republic of China; 3State Key Laboratory of Respiratory Disease & Guangzhou Institute of Respiratory Health & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China; 4Guangzhou National Laboratory, Guangzhou, People’s Republic of China; 5Department of Pulmonary and Critical Care Medicine, Shenzhen Longgang District Central Hospital, Shenzhen, People’s Republic of China; 6Department of Internal Medicine, Guangdong Province Second People’s Hospital, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Fan Wu; Pixin Ran, State Key Laboratory of Respiratory Disease & Guangzhou Institute of Respiratory Health & National Center for Respiratory Medicine & National Clinical Research Center for Respiratory Disease & The First Affiliated Hospital of Guangzhou Medical University, 195 Dongfeng Xi Road, Guangzhou, 510120, People’s Republic of China, Email wu.fan@vip.163.com; pxran@gzhmu.edu.cnBackground: It is unclear whether patients with Global Initiative for Chronic Obstructive Lung Disease stage 1 (mild) chronic obstructive pulmonary disease (COPD) have a higher risk of all-cause mortality than participants with normal spirometry results.Methods: We used the data from the National Health and Nutrition Examination Survey (NHANES) III and 2007– 2012, which included participants aged 20– 79 years, to investigate whether patients with mild COPD (whole population and subgroups) have a higher risk of all-cause mortality than participants with normal spirometry. …”
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    TRACE Model: Predicting Treatment Response to Transarterial Chemoembolization in Unresectable Hepatocellular Carcinoma by Wang W, Zhang Q, Cui Y, Zhang S, Li B, Xia T, Song Y, Zhou S, Ye F, Xiao W, Cao K, Chi Y, Qu J, Zhou G, Chen Z, Zhang T, Chen X, Ju S, Wang YC

    Published 2025-01-01
    “…Weilang Wang,1,* Qi Zhang,2,* Ying Cui,1,* Shuhang Zhang,1 Binrong Li,1 Tianyi Xia,1 Yang Song,3 Shuwei Zhou,1 Feng Ye,4 Wenbo Xiao,5 Kun Cao,6 Yuan Chi,7 Jinrong Qu,8 Guofeng Zhou,9,10 Zhao Chen,11 Teng Zhang,12 Xunjun Chen,13 Shenghong Ju,1 Yuan-Cheng Wang1 1Department of Radiology, Zhongda Hospital, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China; 2Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, People’s Republic of China; 3MR Scientific Marketing, Siemens Healthineers Ltd, Shanghai, People’s Republic of China; 4Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 5Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People’s Republic of China; 6Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, People’s Republic of China; 7Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People’s Republic of China; 8Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, People’s Republic of China; 9Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China; 10Shanghai Institute of Medical Imaging, Shanghai, People’s Republic of China; 11Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 12Institute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, People’s Republic of China; 13Department of Radiology, The People’s Hospital of Xuyi County, Huaian, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yuan-Cheng Wang, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, 87 Ding Jia Qiao Road, Nanjing, Jiangsu, 210009, People’s Republic of China, Tel +086 25 83272121, Fax +086 25 83311083, Email yuancheng_wang@seu.edu.cnPurpose: To develop and validate a predictive model for predicting six-month outcome by integrating pretreatment MRI features and one-month treatment response after TACE.Methods: A total of 108 patients with 160 hCCs from a single-arm, multicenter clinical trial (NCT03113955) were analyzed and served as the training cohort. …”
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