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    Exploring Self-Management Behavior Profiles in Patients with Multimorbidity: A Sequential, Explanatory Mixed-Methods Study by Fu Y, Wu J, Guo Z, Shi Y, Zhao B, Yu J, Chen D, Wu Q, Xue E, Du H, Zhang H, Shao J

    Published 2025-01-01
    “…Yujia Fu,1,2,* Jingjie Wu,3,* Zhiting Guo,4 Yajun Shi,1 Binyu Zhao,1,2 Jianing Yu,1,2 Dandan Chen,3 Qiwei Wu,1,2 Erxu Xue,3 Haoyang Du,3 Huafang Zhang,1 Jing Shao1,2 1Department of Nursing, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, People’s Republic of China; 2School of Nursing and Institute of Nursing Research, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 3Department of Nursing, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 4Department of Nursing, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, Zhejiang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jing Shao, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, 310058, People’s Republic of China, Email 11318202@zju.edu.cnPurpose: This study aims to identify self-management behavior profiles in multimorbid patients, and explore how workload, capacity, and their interactions influence these profiles.Patients and Methods: A sequential explanatory mixed-methods design was employed. …”
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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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